• Bulletin of the Korean Chemical Society
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• v.31 no.6
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• pp.1469-1473
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• 2010

Influences of alrylamino (R) substituents on the herbicidal activity ($pI_{50}$) of 1-(4-chloro-2-fluoro-5-propargyloxypheny)-3-(R)-thiourea analogues (1 ~ 35) against the barnyard grass (Echinochloa crusgalli) in the pre-emergence step were discussed quantitatively using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) as the three dimensional quantitative structure-activity relationship (3D-QSAR) method. The statistically most satisfactory CoMFA models for the herbicidal activity against the barnyard grass had the better predictability ($r^2{_{cv.}}$) and correlativity ($r^2{_{ncv.}}$) than those of CoMSIA models. The optimized CoMFA model 1($r^2{_{cv.}}$ = 0.531 & $r^2{_{ncv.}}$ = 0.931) with the sensitivity to the perturbation (${d_q}^{2'}{dr^2}_{yy'}$ = 1.081) and the prediction ($q^2$ = 0.475) produced by a progressive scrambling analyses were not dependent on chance correlation. And statistical qualities with the atom based fit alignment (AF) were slightly higher than those of the field fit alignment (FF). According to the optimized CoMFA model 1, the contribution ratio (%) of the steric field (76.9%) on the herbicidal activity of the Thioureas was three-fold higher than that of the electrostatic field (20.1%) and the hydrophobic field (3.0%) had the least influence. A steric favor group is on the vicinity of the nitrogen atom in alrylamino (R) substituent, and a steric disfavor group is on the outer side of alrylamino (R) substituent. Thus, as the size of alrylamino (R) substituent increases, so does the herbicidal activity of the substituent.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.376-383
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• 2012

A number of scientific researches are currently being conducted on the potential health hazards of power frequency electric and magnetic field (EMF). There exists a non-objective and psychological belief that they are harmful, although no scientific and objective proof of such exists. This possible health risk from ELF magnetic field (MF) exposure, especially for children under 17 years of age, is currently one of Korea's most highly contested social issues. Therefore, to assess the magnetic field exposure levels of those children in their general living environments, the personal MF exposure levels of 436 subjects were measured for about 6 years using government funding. Using the measured database, estimation formulas were developed to predict personal MF exposure levels. These formulas can serve as valuable tools in estimating 24-hour personal MF exposure levels without directly measuring the exposure. Three types of estimation formulas were developed by applying evolutionary computation methods such as genetic algorithm (GA) and genetic programming (GP). After tuning the database, the final three formulas with the smallest estimation error were selected, where the target estimation error was approximately 0.03 ${\mu}T$. The seven parameters of each of these three formulas are gender (G), age (A), house type (H), house size (HS), distance between the subject's residence and a power line (RD), power line voltage class (KV), and the usage conditions of electric appliances (RULE).

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2843-2845
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• 2000

A lane detection based on a road model or feature all need correct acquirement of information on the lane in a image, It is inefficient to implement a lane detection algorithm through the full range of a image when being applied to a real road in real time because of the calculating time. This paper defines two searching range of detecting lane in a road, First is searching mode that is searching the lane without any prior information of a road, Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It is allow to extract accurately and efficiently the edge candidates points of a lane as not conducting an unnecessary searching. By means of removing the perspective effect of the edge candidate points which are acquired by using the inverse perspective transformation, we transform the edge candidate information in the Image Coordinate System(ICS) into the plane-view image in the World Coordinate System(WCS). We define linear approximation filter and remove the fault edge candidate points by using it This paper aims to approximate more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.

• Korean Chemical Engineering Research
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• v.45 no.6
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• pp.582-590
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• 2007

In view of the analysis of the phenomena and the prediction of the performance, mathematical modelling and simulation of a high temperature pilot reactor for water gas shift reaction (WGSR) has been carried out. Multiscale simulation incorporated computational fluid dynamics (CFD) technique, which has the capability to deal with the reactor shape, fluid and energy transport with extensive degree of accuracy, and process modeling technique, which, in turn is responsible for reaction kinetics and mass transport. This research employed multiscale simulation and the results were compared with those from process simulation. From multiscale simulation, the maximum conversion of was predicted approximately 0.85 and the maximum temperature at the reactor was calculated 720 K, resulting from the heat of reaction. Dynamic simulation was also performed for the time transient profile of temperature, conversion, etc. Considering the results, it is concluded that multiscale simulation is a safe and accurate technique to predict reactor behaviors, and consequently will be available for the design of commercial size chemical reactors as well as other commercial unit operations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.2
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• pp.59-68
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• 1987

Several series of fracture tests were conducted to explore the fracture characteristics and to determine the fracture energy of concrete. A stable three-point bend test was employed to generate the load-deflection curves. The fracture energy may then be calculated from the area under the complete load-deflection curve. The initial notch-to-beam depth ratio (${\alpha}_0$/H) was varied from zero to 0.6. The prediction formula for the fracture energy of concrete is also derived and is found to depend on the tensile strength and aggregate size. The proposed fracture energy formula can be used for the fracture analysis of concrete structures. The present study also devises an equivalent crack length concept to predict the maximum failure loads of concrete beams. A simple formula for the equivalent crack length is proposed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.2
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• pp.141-153
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• 1987

The prediction of the exact behavior of multistory building is one of the most complicated problem encountered in structural engineering practice. An efficient computer method for the three dimensional analysis of building structures is presented in this paper. A multistory building is idealized as an assemblage of a series of rectangular plane frames interconnected by rigid floor diaphragms. The matrix condensation technique is employed for the reduction of degrees of freedom, which results in a significant saving in computational efforts and the required memory size. Kinematical approach was used to assemble condensed stiffness matrices of plane frames into a three dimensional stick model stiffness matrix. The static analysis follows the modified tridiagonal approach. Since this procedure utilizes the condensed stiffness matrix of the structure, the dynamic equations of motion for the story displacement are developed by assigning proper mass for each story. Analysis results of several example structures are compared to those obtained by using the well-known SAP IV for verification of the accuracy and efficiency of the computer program PFS which was developed utilizing the method proposed in this study. The analysis method proposed in this study can be used as an efficient and economical means for the analysis of multistory buildings.

• Computers and Concrete
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• v.2 no.1
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• pp.79-96
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• 2005

The use of high-strength concrete (HSC) has significantly increased over the last decade, especially in offshore structures, long-span bridges, and tall buildings. The behavior of such concrete is noticeably different from that of normal-strength concrete (NSC) due to its different microstructure and mode of failure. In particular, the shear capacity of structural members made of HSC is a concern and must be carefully evaluated. The shear fracture surface in HSC members is usually trans-granular (propagates across coarse aggregates) and is therefore smoother than that in NSC members, which reduces the effect of shear transfer mechanisms through aggregate interlock across cracks, thus reducing the ultimate shear strength. Current code provisions for shear design are mainly based on experimental results obtained on NSC members having compressive strength of up to 50MPa. The validity of such methods to calculate the shear strength of HSC members is still questionable. In this study, a new approach based on artificial neural networks (ANNs) was used to predict the shear capacity of NSC and HSC beams without shear reinforcement. Shear capacities predicted by the ANN model were compared to those of five other methods commonly used in shear investigations: the ACI method, the CSA simplified method, Response 2000, Eurocode-2, and Zsutty's method. A sensitivity analysis was conducted to evaluate the ability of ANNs to capture the effect of main shear design parameters (concrete compressive strength, amount of longitudinal reinforcement, beam size, and shear span to depth ratio) on the shear capacity of reinforced NSC and HSC beams. It was found that the ANN model outperformed all other considered methods, providing more accurate results of shear capacity, and better capturing the effect of basic shear design parameters. Therefore, it offers an efficient alternative to evaluate the shear capacity of NSC and HSC members without stirrups.

• Computers and Concrete
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• v.13 no.6
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• pp.739-748
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• 2014

In this article, by using experimental studies and artificial neural network has been tried to investigate the use of nano-silica as concrete admixture to reduce alkali-silica reaction. If there are reactive aggregates and alkali of cement with enough moisture in concrete, a gel will be formed. Then with high reactivity between alkali of cement and existence of silica in aggregates, this gel will expand by absorption of water, and causes expansive pressure and cracks be formed. At the time passes, this gel will reduce both durability and strength of the concrete. By reducing the size of silicate to nano, specific surface area of particles and number of atoms on the surface will be increased, which causes more pozzolanic activity of them. Nano-silica can react with calcium hydroxide ($Ca(OH)_2$) and produces C-S-H gel. In this study, accelerated mortar bar specimens according to ASTM C 1260 and ASTM C 1567, with different mix proportions were prepared using aggregates of Kerman, such as: none admixture and plasticizer, different proportions of nano-silica separately. By opening the moulds after 24 hour and curing in water at $80^{\circ}C$ for 24 hour, then curing in (1N NaOH) at $80^{\circ}C$ for 14 days, length expansion of mortar bars were measured and compared. It was noted that, the lowest length expansion of a specimens shows the best proportion of admixture based on alkali-silica reactivity. Then, prediction of alkali-silica reaction of concrete has been investigated by using artificial neural network. In this study the backpropagation network has been used and compared with different algorithms to train network. Finally, the best amount of nano silica for adding to mix proportion, also the best algorithm and number of neurons in hidden layer of artificial neural network have been offered.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1951-1956
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• 2004

The transient nature and complex flow geometries of two-phase gas-liquid flows cause fundamental difficulties when measuring flow velocity using an electromagnetic flowmeter. Recently, a current-sensing flowmeter was introduced to obtain measurements with high temporal resolution (Ahn et $al.^{(1)}$). In this study, current-sensing flowmeter theory was applied to measure the fast velocity transients in slug flows. To do this, the velocity fields of axisymmetric gas-liquid slug flow in a vertical pipe were obtained using Volume-of-Fluid (VOF) method and the virtual potential distributions for the electrodes of finite size were also computed using the finite volume method for the simulated slug flow. The output signal prediction for slug flow was carried out from the velocity and virtual potential (or weight function) fields. The flowmeter was numerically calibrated to obtain the cross-sectional liquid mean velocity at an electrode plane from the predicted output signal. Two calibration parameters are required for this procedure: a flow pattern coefficient and a localization parameter. The flow pattern coefficient was defined by the ratio of the liquid resistance between the electrodes for two-phase flow with respect to that for single-phase flow, and the localization parameter was introduced to avoid errors in the flowmeter readings caused by liquid acceleration or deceleration around the electrodes. These parameters were also calculated from the computed velocity and virtual potential fields. The results can be used to obtain the liquid mean velocity from the slug flow signal measured by a current-sensing flowmeter.

• The Journal of Fisheries Business Administration
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• v.36 no.3 s.69
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• pp.89-117
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• 2005

Currently, the tax - exempted vessel fuel is provided for commercial fishing in order to increase the competitive power of fishery production thorough the National Federation of Fisheries Cooperatives. The National Federation of Fisheries Cooperatives should predict the exact amount of fuel consumption for fishing every year to request the fuel from the government. Unfortunately, there is no sophisticated model to predict the tax - exempted vessel fuel consumption. In 2003, the consumption of the tax- exempted vessel fuel was only $25.1\%$ of the estimation amount by the National Federation of Fisheries Cooperatives. This causes an inefficiency in the petroleum management. Moreover, we need some data such as the annual average fishing hours, fishing days and fishing behavior to adopt a new policy regarding fishing. Up to now, the data have been obtained by survey with response in the fishery field. In the most case, we have a small number of data because we spend so much time and money consuming for collecting fishing data. As a result, the level of confidence of the data is associated with the sample size and normally low. In order to achieve more accurate data, we need to develope an efficient method for collecting fishing data. In this research, we proposed a new method to predict the tax- exempted vessel fuel consumption more exactly. The prediction results from the proposed method has been compared with the results from the current method. According to the results in this research, the method proposed here produced much better accuracy than the current method. In addition, we also proposed in the paper for collecting fishing data of the annual average fishing hours using the tax - exempted vessel fuel consumption and the gasoline consumption of vessel engine. The fishing data obtained by using the method proposed in this research could be much more efficient and accurate because it doesn't need to estimate from survey sample data.