• Analytical Science and Technology
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• v.16 no.6
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• pp.483-487
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• 2003

Amitrole is well-known as a non-selective herbicide and it is able to cause contamination of driking water as well as pollution of ground water and surface water. However, it is difficult to extract from water because it has a high solubility for water whereas a low solubility for general organic solvents. This method is described for the determination of amitrole in water samples by GC/MS. After evaporation of 10 mL water sample by a vacuum evaporator, amitrole was derivatized with isobutyl chloroformate (iso-BCF) on room temperature for 15~20 min. As a result, the sensitivity for GCfMS was improved as N-isobutoxycarbonyl amitrole derivative was formed. The linearity of the calibration curve showed good as 0.997. The recoveries were obtained more than 94.9% and relative standard deviations were less than 2.8% at $1.0{\mu}g/L$, $10.0{\mu}g/L$ and $100.0{\mu}g/L$. The limit of detection showed $0.1{\mu}g/L$ with a signal-to-noise ratio (S/N) of 3.

• Analytical Science and Technology
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• v.29 no.5
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• pp.242-247
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• 2016

This research aims to set up and validate methods of analyzing the methanol in wet wipes and verifies the analysis methods that applied to the wet wipes. We used Headspace (HS) Gas Chromatography (GC) - Flame Ionization Detector (FID) to the establish analysis method of methanol in wet wipes and optimized heating temperature, heating time, GC conditions with column. The result indicated that 3 mL of sample in 20 mL headspace vial can be equilibrated efficiently in headspace sampler at 70 ℃ for 10 min and sample was measured by GC with spli injection mode(10:1). The results show that linearity from 1 to 100 ppm was over R2 0.9995, precision was RSD 1.83 % and accuracy(recovery rate) was 105.44 (±1.05 %) on water matrix and wet wipes matrix removed non-woven fabric. Also, monitoring results of total 20 cosmetics on the market, from 0.00017 to 0.00156 % of methanol was detected from wet wipes.

• Applied Chemistry for Engineering
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• v.24 no.6
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• pp.656-662
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• 2013

The iron oxide ($Fe_3O_4$) particles in the coolant of the secondary system of a nuclear power plant reduce the heat transfer performance or induce corrosion on the surface of the heat transfer tube. To prevent these problems, we conducted a study to improve the dispersion stability of iron oxide using polymeric dispersant injection in simulated secondary system water. The three kinds of anionic polymers containing carboxyl groups were selected. The dispersion characteristics of the iron oxide particles with the polymeric dispersants were evaluated by performing a settling test and measuring the transmission, the zeta potential, and the hydrodynamic particle size of the colloid solutions. Polymeric dispersants had a significant impact on the iron oxide dispersion stability in an aqueous solution. While the dispersant injection tended to improve the dispersion stability, the dispersion stability of iron oxide did not increase linearly with an increase in the dispersant concentration. This non-linearity is due to the agglomerations between the iron oxide particles above a critical dispersant concentration. The effect of the dispersant on the dispersion stability improvement was significant when the dispersant concentration ratio (ppm, dispersant/magnetite) was in the range of 0.1 to 0.01. This suggests that the optimization of dispersant concentration is required to maximize the iron oxide removal effect with the dispersant injection considering the applied environments, the iron oxide concentration and the concentration ratio of dispersant to iron oxide.

• Korean Journal of Food Science and Technology
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• v.31 no.2
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• pp.385-390
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• 1999

Noodle was made using a combination of yulmu, wheat and water through mixture design. Statistical models of yulmu noodle were shown by analysing tensile stress and color $(L^{*})$, and sensory evaluation with other constraints. Analysing the linear and non-linear model, the linearity in the values of tensile stress, lightness $(L^{*})$ and sensory evaluation showed that each component worked separately without interactions. In studying the component effect on the response by trace plot, the result indicated that the increase in the amount of yulmu enhanced tensile stress of noodle while degrading $L^{*}$ value and sensory evaluation score. In the range of satisfying the conditions of noodle in every tensile stress, $L^{*}$ value and sensory evaluation point, the optimum mixture ratio of yulmu : wheat : water was 2.27% : 66.28% : 28.45% based on least cost linear programming. In this calculation, the least cost was 9.924 and estimated potential results of the response for tensile stress was 2.234 N and those for $L^{*}$ was 82.39. Finally, the potential response results affected by mixture ratio of yulmu, wheat and water were screened using Excel.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.137-143
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• 2015

A delay-line type time-to-digital converter (TDC) implemented in a field-programmable gate array (FPGA) is most widely owing due to its simple structure and high conversion rate. However, the delay-line type TDC suffers from nonlinearity error caused by the long delay-line because its time interval measurement range is determined by the length of the used delay line. In this study, a new TDC structure with a shorter delay line by taking a pulse train as an input is proposed for improved time accuracy and efficient use of resources. The proposed TDC utilizes a pulse-train with four transitions and a transition state detector that identifies the used transition among four transitions and prevents the meta-stable state without a synchronizer. With 72 delay cells, the measured resolution and maximum non-linearity were 20.53 ps, and 1.46 LSB, respectively, and the time interval measurement range was 5070 ps which was enhanced by approximately 343 % compared to the conventional delay-line type TDC.

• Journal of Korean Association for Spatial Structures
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• v.7 no.2 s.24
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• pp.91-96
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• 2007

To improve the land use of urban, Construction of the circular steel column is required recently. The circular steel columns have a advantage for improving a load carrying capacity as wall as reducing a effective section area. However, the circular steel columns under service load, such as earthquake, shows a tendency to cause local buckling and large deformation. To prevent these phenomena, use of diaphragm is considered. It is reported that longitudinal stiffeners has a effect on improving a buckling and fatigue performance of steel structures. The research of effect on diaphragm is not sufficient. Under monotonic and cyclic loadings diaphragm make a important role to prevent local buckling and deformation of used steel structures. Therefore, influence of diaphragm on performance of used steel structures is investigated. In this study, the influence of diaphragm on seismic and deformation performance of circular steel piers was investigated by using elastic-plastic finite element analysis considered geometrical and material non-linearity. The seismic performance of circular steel columns was evaluated for analytical parameter of manufactured part. The seismic performance of circular steel columns was clarified by comparing an energy dissipation of circular steel piers.

• Journal of the Korean Chemical Society
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• v.39 no.12
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• pp.902-909
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• 1995

Detection limit as well as calibration curves on organophosphorus pesticide(dimethoate, diazinon, parathion-methyl, fenitrothion, malathion) and BHCs were measured for evaluation of utility on qualitative or quantitative analysis of pesticides with ion Trap mass spectrometer and quadrupole mass spectrometer. As ionization source, EI and CI were adopted for qualitative analysis of pesticides by comparison of each fragmentation pattern. At the same time, the utility as trace analysis techniques through scan or selected ion monitoring(SIM) mode was evaluated. With ion trap for all pesticides, detection limit(DL, 1 ${\mu}L$ injection) on scan mode was ranged 0.008∼0.225 ng at signal to noise ratio 3. With quadrupole DL on scan mode was ranged 0.23∼3.1 ng over 0.032∼0.68 ng on SIM mode. The calibration curve with ion trap generated good linearity over 0.99 as correlation coefficient. As clean up procedure, Bio Beads S-X3 was used for the separation of oils from five organophosphorous pesticides in flour extractant showing more than 80% as recovery at most cases. In case of BHCs in jinseng with Florisil column, the recovery of pesticides has been 60% to 90%.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.11
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• pp.83-94
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• 2003

In this paper. a highly linear and low glitch CMOS current mode digital-to-analog converter (DAC) by self calibration bias circuit is proposed. The architecture of the DAC is based on a current steering 6＋4 segmented type and new switching scheme for the current cell matrix, which reduced non-linearity error and graded error. In order to achieve a high performance DAC . novel current cell with a low spurious deglitching circuit and a new inverse thermometer decoder are proposed. The prototype DAC was implemented in a 0.35${\mu}{\textrm}{m}$ n-well CMOS technology. Experimental result show that SFDR is 60 ㏈ when sampling frequency is 32MHz and DAC output frequency is 7.92MHz. The DAC dissipates 46 mW at a 3.3 Volt single power supply and occupies a chip area of 1350${\mu}{\textrm}{m}$ ${\times}$750${\mu}{\textrm}{m}$.

• Journal of the Korean GEO-environmental Society
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• v.2 no.1
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• pp.103-114
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• 2001

Sorption studies were conducted to determine if slow sorption fraction is observed in recent1y deposited organic matter by studying wetland soils explicitly. Sorption characteristics of hydrophobic organic compounds (chlorobenzene and phenanthrene) in recently deposited freshwater marsh soils were determined using a batch sorption procedure. Relative indicators of organic matter age were assessed using several techniques including the ratio of elemental oxygen to carbon in the organic matter. Slow sorption characteristics for both surface marsh soil (top 0-2 cm, <5 years old) and deeper marsh soil (below 10-cm, >20 years old) were compared against relatively older PPI (Petro Processors, Inc. Superfund site) and BM (Bayou Manchac) soils to investigate whether soil age can cause differences in sorption of organic compounds in wetland soils. Increases in sorption non-linearity of slow sorption model parameters (increase in KF and decrease in N) explain the existence of slow sorption fraction. The results of slow sorption model indicates the presence of a sizable slow sorption fraction; 25.4 - 26.3% (chlorobenzene) and 1.4 - 1.9% (phenanthrene) of the sorbed mass in wetland soils and 40.0 - 55.93% (chlorobenzene) and 2.9 - 3.19% (phenanthrene) of the sorbed mass in PPI and BM soils, respectively. The slow sorption fraction increased in the order of surface < deeper < PPI < BM soil indicating that size of the slow sorption fraction increases with soil organic matter age.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.