• Computers and Concrete
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• v.27 no.4
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• pp.319-332
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• 2021

The performance of gene expression programming (GEP) in predicting the compressive strength of bacteria-incorporated geopolymer concrete (GPC) was examined in this study. Ground-granulated blast-furnace slag (GGBS), new bacterial strains, fly ash (FA), silica fume (SF), metakaolin (MK), and manufactured sand were used as ingredients in the concrete mixture. For the geopolymer preparation, an 8 M sodium hydroxide (NaOH) solution was used, and the ambient curing temperature (28℃) was maintained for all mixtures. The ratio of sodium silicate (Na2SiO3) to NaOH was 2.33, and the ratio of alkaline liquid to binder was 0.35. Based on experimental data collected from the literature, an evolutionary-based algorithm (GEP) was proposed to develop new predictive models for estimating the compressive strength of GPC containing bacteria. Data were classified into training and testing sets to obtain a closed-form solution using GEP. Independent variables for the model were the constituent materials of GPC, such as FA, MK, SF, and Bacillus bacteria. A total of six GEP formulations were developed for predicting the compressive strength of bacteria-incorporated GPC obtained at 1, 3, 7, 28, 56, and 90 days of curing. 80% and 20% of the data were used for training and testing the models, respectively. R2 values in the range of 0.9747 and 0.9950 (including train and test dataset) were obtained for the concrete samples, which showed that GEP can be used to predict the compressive strength of GPC containing bacteria with minimal error. Moreover, the GEP models were in good agreement with the experimental datasets and were robust and reliable. The models developed could serve as a tool for concrete constructors using geopolymers within the framework of this research.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.159-166
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• 2017

In this paper, we have experimented to improve the verification performance of speaker change detection on broadcast news. It is to enhance the input noisy speech and to apply the KL distance $D_s$ using the SNR-based weighting function $w_m$. The basic experimental system is the verification system of speaker change using GMM-UBM based KL distance D(Experiment 0). Experiment 1 applies the input noisy speech enhancement using MMSE Log-STSA. Experiment 2 applies the new KL distance $D_s$ to the system of Experiment 1. Experiments were conducted under the condition of 0% MDR in order to prevent missing information of speaker change. The FAR of Experiment 0 was 71.5%. The FAR of Experiment 1 was 67.3%, which was 4.2% higher than that of Experiment 0. The FAR of experiment 2 was 60.7%, which was 10.8% higher than that of experiment 0.

• Journal of the Korea Concrete Institute
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• v.14 no.4
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• pp.457-466
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• 2002

An artificial neural network was applied to predict compressive strength, slump value and mix proportion of a concrete. Standard mixed tables were trained and estimated, and the results were compared with those of the experiments. To consider variabilities of material properties, the standard mixed fables from two companies of Ready Mixed Concrete were used. And they were trained with the neural network. In this paper, standard back propagation network was used. The mix proportion factors such as water cement ratio, sand aggregate ratio, unit water, unit cement, unit weight of sand, unit weight of crushed sand, unit coarse aggregate and air entraining admixture were used. For the arrangement on the approval of prediction of mix proportion factor, the standard compressive strength of $180kgf/cm^2{\sim}300kgf/cm^2$, and target slump value of 8 cm, 15 cm were used. For the arrangement on the approval of prediction of compressive strength and slump value, the standard compressive strength of $210kgf/cm^2{\sim}240kgf/cm^2$, and target slump value of 12 cm and 15 cm wore used because these ranges are most frequently used. In results, in the prediction of mix proportion factor, for all of the water cement ratio, sand aggregate ratio, unit water, unit cement, unit weight of sand, unit weight of crushed sand, unit coarse aggregate, air entraining admixture, the predicted values and the values of standard mixed tables were almost the same within the target error of 0.10 and 0.05, regardless of two companies. And in the prediction of compressive strength and slump value, the predicted values were converged well to the values of standard mixed fables within the target error of 0.10, 0.05, 0.001. Finally artificial neural network is successfully applied to the prediction of concrete mixture and compressive strength.

• Fire Science and Engineering
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• v.24 no.6
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• pp.139-144
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• 2010

Fire fighting foam is expanded when it mix with many water in mechanical method. It have adaptability, mass production possibility, long-time storage possibility. But foam isn't recommended that it use for extinguish the fire in winter. Because of, expansion ratio is changed according to exterior temperature and environment. In this study, we analysis to effect of expansion according to temperature and develop auto mixing system available for fire engine. As a result of non-standard drug mixture is 3.0% up to 30.08% depending on the temperature of the fire showed that the difference in performance occurs. In addition, analysis of the applicability of automatic mixing system design values and actual experimental data as 0.012% maximum error of the applicability of the system obtained according nataname was judged.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1083-1096
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• 2015

This study utilised Computational Fluid Dynamics(CFD) for preliminary assessment of mixing efficiencies of 2-phase fluids in a pipe at which a slurry flow and an injected solidifier join, for the purposes of reducing trial-and-error-based instances of physical experiments and conducting the overall research in an economical way. Using OpenFOAM$^{(R)}$, we simulated behavior of 3-phase fluids under 18 different settings generated by changing diameters of a dredged soil transportation pipe, a quality improving material injection pipe and the confluence angle. While difference in mixing efficiencies amongst the instances was insignificant, discernible boundary layers amongst the materials were observed in all of the instances. In order to break the boundary layers, we designed a substructure inside a pipe and found out that it could remarkably improve mixing efficiencies particularly for short distance applications.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.585-589
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• 2010

It is important for the liquid rocket engine to meet the exact performance requirements in order to guarantee the successful mission of the launch vehicle. Usually, a ground combustion test for the engine is conducted to reduce the performance error and for the tuning. For the gas-generator (GG) cycle engine, this adjustment process can be easily tuned by means of the control valves. A linearized correlation between the process parameters of the control - the combustion chamber pressure and the mixture ratio of engine - and the independent parameter of the control- rotational angle of the control valve - could be suitable to reduce the tuning errors. Also this linearity can reduce the effort for the tuning and make the process more explicit by ensuring a more intuitive control. In this point, we proposed an algorithm in the frame of the in-house-developed program to obtain the control valves' inherent characteristics which satisfy the linearity.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.226-233
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• 2023

To create an environmentally sustainable fuel with a low sulfur concentration, requires alternative sulfur removal methods. During the course of this study, a high surface gamma alumina-supported ZnO nanocatalyst with a ZnO/-Al₂O₃ ratio of 12% was developed and tested for its ability to improve the activity of the oxidative desulfurization (ODS) process for the desulfurization of kerosene fuel. Scanning electron microscopy (SEM) and Brunauer-Emmett-Teller (BET) were used to characterize the produced nanocatalyst. In a digital batch baffled reactor (20~80 min), the effectiveness of the synthesized nanocatalyst was tested at different initial concentrations of dibenzothiophene (DBT) of 300~600 ppm, oxidation temperatures (25~70 ℃), and oxidation periods (0.5, 1, and 2 hours). The baffles included in the digital baffled batch reactor resist the swirling of the reaction mixture, thus facilitating mixing. The ODS procedure yielded the maximum DBT conversion (95.5%) at 70 ℃ with an 80-minute reaction time and an initial DBT level of 600 ppm. The most precise values of kinetic variables were subsequently determined using a mathematical modelling procedure for the ODS procedure. The average absolute error of the simulation findings was less than 5%, demonstrating a good degree of agreement with the experimental results acquired from all runs. The optimization of the operating conditions revealed that 99.1% of the DBT can be removed in 140 minutes.

• Journal of the Korea Concrete Institute
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• v.25 no.1
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• pp.115-123
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• 2013

The steel industry, a representative industry that significantly consumes raw materials and energy, produces steel as well as a large amount of by-product steel slag through the production process. The vast habitat foundation of marine life has been destroyed due to recent reckless marine development and environment pollution, resulting in intensification of the decline of marine resources, and a solution to this issue is imperative. In order to propose a method to recycle large amounts of by-product slag into a material that can serve as an alternative to natural aggregate, the engineering properties and applicability for each mixing factor of environment friendly porous concrete as a material for the composition of marine ranches were evaluated in this study. The test results for percentage of voids per mixing ratio revealed that the margin of error for all conditions was within 2.5%. The compressive strength test results showed that the most outstanding environmental friendly porous concrete can be manufactured when mixing 30% slag aggregate and 10% specially treated granular fertilizer for the optimum volume fraction. As concrete for marine applications, the best seawater resistance was obtained with mixing conditions for high compression strength. An assessment of the ability to provide a marine life habitat foundation of environmentally friendly porous concrete showed that a greater percentage of voids facilitated implantation and inhabitation of marine life, and the mixing of specially treated granular fertilizer led to active initial implantation and activation of inhabitation. The evaluation of harmfulness to marine life depending on the mixture of slag aggregate and specially treated granular fertilizer revealed that the stability of fish is secured.

• Progress in Medical Physics
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• v.10 no.1
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• pp.23-32
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• 1999

Combined MRI and Relaxogram approach was introduced as a very useful tool for fat study. The phantoms simulating homogeneous mixture of fat and non-fat environments were measured with spin echo pulse sequence on a 0.15 T whole body imager. From 45 scans, the Tl values were obtained by fitting the data to continuous distribution (CONTIN) of relaxation time. This relaxogram gives broad distributions of relaxation time, which are characterized by a number of peaks with characteristic T1 values. Two distinct peaks in relaxogram were observed and identified as signals from com oil and gelatin gel. This model system can be served as simulating the distribution of fat in muscle. Also the relative ratio of two components, which is proportional to the area under the peak, is estimated and compared to nominal values. Based on the good agreement between two predictions, the values from our proposed method agreed with nominal values within $\pm$7 % error. The effects of different concentration of contrast agent and different region of interest are presented. To optimize total scan times, the minimum required data points and so further reduction in total scan times are discussed.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.7
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• pp.1054-1060
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• 2017

Objective: This study was aimed at evaluating effects of cattle breed resources and alternative mixed-feeding practices on meat productivity and emission intensities from household farming systems (HFS) in Daklak Province, Vietnam. Methods: Records from Local $Yellow{\time}Red$ Sindhi (Bos indicus; Lai Sind) and 1/2 Limousin, 1/2 Drought Master, and 1/2 Red Angus cattle during the growth (0 to 21 months) and fattening (22 to 25 months) periods were used to better understand variations on meat productivity and enteric methane emissions. Parameters were determined by the ruminant model. Four scenarios were developed: (HFS1) grazing from birth to slaughter on native grasses for approximately 10 h plus 1.5 kg dry matter/d (0.8% live weight [LW]) of a mixture of guinea grass (19%), cassava (43%) powder, cotton (23%) seed, and rice (15%) straw; (HFS2) growth period fed with elephant grass (1% of LW) plus supplementation (1.5% of LW) of rice bran (36%), maize (33%), and cassava (31%) meals; and HFS3 and HFS4 computed elephant grass, but concentrate supplementation reaching 2% and 1% of LW, respectively. Results: Results show that compared to HFS1, emissions ($72.3{\pm}0.96kg\;CH_4/animal/life$; least squares $means{\pm}standard$ error of the mean) were 15%, 6%, and 23% lower (p<0.01) for the HFS2, HFS3, and HFS4, respectively. The predicted methane efficiencies ($CO_2eq$) per kg of LW at slaughter ($4.3{\pm}0.15$), carcass weight ($8.8{\pm}0.25kg$) and kg of edible protein ($44.1{\pm}1.29$) were also lower (p<0.05) in the HFS4. In particular, irrespective of the HSF, feed supply and ratio changes had a more positive impact on emission intensities when crossbred 1/2 Red Angus cattle were fed than in their crossbred counterparts. Conclusion: Modest improvements on feeding practices and integrated modelling frameworks may offer potential trade-offs to respond to climate change in Vietnam.