• Computers and Concrete
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• 제32권2호
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.

• 한국토양비료학회지
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• 제31권4호
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• pp.359-367
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• 1998

미국 Pennsylvania주 옥수수 재배 토양의 질소공급능력을 1986년부터 3년간 수행되었던 47개 토양의 화학성 및 정밀 토양도 속성들과의 회귀분석으로 평가 비교하였다. 질소공급능력과 가장 밀접한 상관을 보인 화학성은 $NO_3-N$ 함량($R^2=0.518$)이었으나 질소공급능력에 대한 표준화 편회귀계수는 년차간 변이를 보이며 0.578로 다른 성질들과 큰 차이를 보이지 않았다. 질소공급능력에 대한 다중선형 회귀분석은 단순 회귀분석에 비하여 양호한 평가를 보였으며 화학성들에 의한 결정계수는 $R^2=0.599$, 화학성과 Ap층 깊이의 정량적 지표들에 의한 계수는 $R^2=0.698$, 정량적 지표들과 정성적 지표들에 의한 계수는 $R^2=0.839$로 증가되었다. 이는 다중선형 회귀모델식이 단순 회귀모델식보다 토양의 질소공급능력을 보다 신뢰성 있게 평가할 수 있는 접근방법임을 보여주었다.

• Computers and Concrete
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• 제14권3호
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• pp.233-245
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• 2014

In this paper, a rule based Mamdani type fuzzy logic model for prediction of slippage at maximum tensile strength and slippage at rupture of structural lightweight concretes were discussed. In the model steel rebar diameters and development lengths were used as inputs. The FL model and experimental results, the coefficient of determination R2, the Root Mean Square Error were used as evaluation criteria for comparison. It was concluded that FL was practical method for predicting slippage at maximum tensile strength and slippage at rupture of structural lightweight concretes.

• 농업과학연구
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• 제46권1호
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• pp.183-194
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• 2019

Adulteration of argan oil with some other cheaper oils with similar chemical compositions has resulted in increasing demands for authenticity assurance and quality control. Fast and simple analytical techniques are thus needed for authenticity analysis of high-priced argan oil. Raman spectroscopy is a potent technique and has been extensively used for quality control and safety determination for food products In this study, Raman spectroscopy in combination with a net analyte signal (NAS)-based methodology, i.e., hybrid linear analysis method developed by Goicoechea and Olivieri in 1999 (HLA/GO), was used to predict the different concentrations of olive oil (0 - 20%) added to argan oil. Raman spectra of 90 samples were collected in a spectral range of $400-400cm^{-1}$, and calibration and validation sets were designed to evaluate the performance of the multivariate method. The results revealed a high coefficient of determination ($R^2$) value of 0.98 and a low root-mean-square error (RMSE) value of 0.41% for the calibration set, and an $R^2$ of 0.97 and RMSE of 0.36% for the validation set. Additionally, the figures of merit such as sensitivity, selectivity, limit of detection, and limit of quantification were used for further validation. The high $R^2$ and low RMSE values validate the detection ability and accuracy of the developed method and demonstrate its potential for quantitative determination of oil adulteration.

• 한국자기학회지
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• 제5권2호
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• pp.109-111
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• 1995

단결정 Cu/ Ni/ Cu 박막의 자기탄성계수(magnetoelastic coupling coefficients)를 자성박막의 두께에 따른 효과이방성에너지(effective anisotropy energy)를 측정하여 현 상학적인 이론 모델로 구하는 방법을 제안하였다. 이러한 간접적인 방법으로 자기탄성 계수를 결정하는 방법은 다른 결정정계에서도 가능하다.

• 한국식품위생안전성학회지
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• 제24권3호
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• pp.232-237
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• 2009

본 연구는 오염된 양상치를 알카리전해수로 세척한 처리구와 비처리구에 오염된 E. coli O157 : H7균이 다양한 온도 (4, 10, 15, 20, 25, 30, $35^{\circ}C$)에 저장할 경우 이균의 specific growth rate (SCR) 과 lag time (LT) 생육변수에 미치는 영향을 조사하기 위한 모델을 개발하기 위하여 수행되었다. E. coli O157 : H7의 specific growth rate (SGR) 과 lag time (LT)를 결정하기 위해 생육도를 Gompertz 식을 사용하여 fitting한 결과, $R^2$값이 0.994로 나타났다. 실험값으로부터 얻은 SGR과 LT는 저장온도에 의존하는 것으로 나타났으며 $4^{\circ}C$에서 $35^{\circ}C$까지 온도가 증가할수록 성장 속도가 증가하는 것으로 나타났다. AIEW 처리구 또는 비처리구의 양상치 에서 E. coli O157 : H7의 성장 kinetics에 대한 저장 온도의 효과를 평가하기 위해 SRG에 대한 두개의 모델을 개발하였다. 유도된 2개의 모델 검증은 $R^2$, $R^2_{Adj}$ (adjusted determination coefficient) 및 MSE (mean square error)를 적용하였으며, 그 결과 $R^2$, $R^2_{Adj}$가 1 (>0.93)에 근접하였으며, 알카리 전해수 처리구 및 비처리구 양상치 모델의 MSE는 각각 0.031, 0.025로 나타났다. 따라서, 본연구에서 개발된 모델의 생육변수는 실험 치에서 얻은 E. coli O157 : H7의 생육변수 결과와 매우 유사한 것으로 나타났다.

• Journal of Biosystems Engineering
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• 제40권3호
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• pp.165-177
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• 2015

Purpose: Accurate monitoring of soil strength is a key technology applicable to various precision agricultural practices. Soil strength has been traditionally measured using a cone penetrometer, which is time-consuming and expensive, making it difficult to obtain the spatial data required for precision agriculture. To improve the current, inefficient method of measuring soil strength, our objective was to develop and evaluate an in-situ system that could measure horizontal soil strength in real-time, while moving across a soil bin. Methods: Multiple cone-shape penetrometers were horizontally assembled at the front of a vertical plow blade at intervals of 5 cm. Each penetrometer was directly connected to a load cell, which measured loads of 0-2.54 kN. In order to process the digital signals from every individual transducer concurrently, a microcontroller was embedded into the measurement system. Wireless data communication was used between a data storage device and this real-time horizontal soil strength (RHSS) measurement system travelling at 0.5 m/s through an indoor experimental soil bin. The horizontal soil strength index (HSSI) measured by the developed system was compared with the cone index (CI) measured by a traditional cone penetrometer. Results: The coefficient of determination between the CI and the HSSI at depths of 5 cm and 10 cm ($r^2=0.67$ and 0.88, respectively) were relatively less than those measured below 20 cm ($r^2{\geq}0.93$). Additionally, the measured HSSIs were typically greater than the CIs for a given numbers of compactor operations. For an all-depth regression, the coefficient of determination was 0.94, with a RMSE of 0.23. Conclusions: A HSSI measurement system was evaluated in comparison with the conventional soil strength measurement system, CI. Further study is needed, in the form of field tests, on this real-time measurement and control system, which would be applied to precision agriculture.

• 한국환경과학회지
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• 제26권6호
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• pp.719-728
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• 2017

In order to investigate the adsorption characteristics for Sr ion using the Na-X zeolite synthesized from coal fly ash, batch tests and response surface analyses were carried out. The adsorption kinetic data for Sr ions, using Na-X zeolite, fitted well with the pseudo-second-order model. The uptake of Sr ions followed the Langmuir isotherm model, with a maximum adsorption capacity of 196.46 mg/g. Thermodynamic studies were conducted at different reaction temperatures, with the results indicating that Sr ion adsorption by Na-X zeolite was an endothermic (${\Delta}H^o$>0) and spontaneous (${\Delta}G^o$<0) process. Using the response surface methodology of the Box-Behnken method, initial Sr ion concentration ($X_1$), initial temperature ($X_2$), and initial pH ($X_3$) were selected as the independent variables, while the adsorption of Sr ions by Na-X zeolite was selected as the dependent variable. The experimental data fitted well with a second-order polynomial equation by multiple regression analysis. The value of the determination coefficient ($R^2=0.9937$) and the adjusted determination coefficient (adjusted $R^2=0.9823$) was close to 1, indicating high significance of the model. Statistical results showed the order of Sr removal based on experimental factors to be initial pH > initial concentration > temperature.

• Journal of Biosystems Engineering
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• 제34권1호
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• pp.15-20
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• 2009

This study was conducted to develop a moisture sensor for rapeseed, a bio-diesel material. A typical rapeseed, SUNMANG, was used as a raw material. The rapeseed moisture content sensor consists of three components, such as upper and bottom electrodes, a test material dish, and a fixing housing. To evaluate the performance, a data acquisition system was equipped with the rapeseed moisture sensor, computer, printer, and main board. The findings of this study were: 1) the rapeseed moisture content was inversely proportional to electric resistance, and 2) values of electric resistance were recorded in a range of $10{\sim}100\;M{\Omega}$, depending upon a change of the moisture content. The determination of coefficient ($R^2$) and standard error between rapeseed moisture content and electric resistance were 0.9921 and ${\pm}0.289$, which indicated a highly correlative relationship. The response of rapeseed moisture sensor to temperature change was also observed for further performance test. Satisfying results were obtained, such as the determination of coefficient ($R^2$) of 0.9918, predicted standard error of ${\pm}0.373%$, deviation of 0.103%, measurement error of $0.14{\sim}0.48%$, standard deviation of $0.01{\sim}0.22%$, and measurement time of 28.3 s per point, respectively.

• 한국환경보건학회지
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• 제35권2호
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• pp.130-142
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• 2009

This study compared FTIR with XRD method for the analysis of quartz by % recovery, coefficient of variation (CV) and influence of the interference. the results were as the following. 1. In FTIR method, the coefficient of determination ($r^2$) was 0.9998 in a calibration curve of $695\;cm^{-1}$, and the limit of detection was $4.9{\mu}g/sample$. 2. The highest recovery was $799\;cm^{-1}$ (98.2%). 3. The CVpooled of the FTIR method was approximately 10% in three wave numbers. 4. The analysis of qualitative and quantitative for quartz is difficult with mixed cristobalite and iron oxide. 5. In XRD method with rotating sample holder and LynxEye detector, the coefficient of determination was 0.9996 in a calibration curve, and the limit of detection was $5.9{\mu}g/sample$. 6. The recovery and CV pooled were 104.3%, and 11 %, respectively. 7. In muffle furnace ashing, the quartz weight decreased to 34% when the maximum weight of the iron oxide was more than eight times. In conclusion, the accuracy (% recovery) and precision (CV) of FTIR and XRD method for analyzing $\alpha$-quartz were similar. FTIR method was a disadvantage for sample matrix because it indicates possibility of interference. However, XRD method distinguished specific crystalline forms of silica, and the majority of silicate minerals. In addition, XRD method recommend filter dissolution to pretreatment method.