• 한국세라믹학회지
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• 제56권2호
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• pp.146-152
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• 2019

In order to study the transport behavior of tripolyphosphate (TPP) in aqueous solutions, the adsorption process of TPP on synthetic goethite, which exists stably in supergene environment, has been systematically studied. The adsorption properties under different conditions (pH, electrolyte presence, and temperature) were investigated. The adsorption of TPP in the presence of humic acid (HA)/fulvic acid (FA) has also been discussed in this paper. The results indicated that the adsorption capacity quickly increased within the first hour and equilibrium was reached within 24 h. The adsorption capacity decreased from 1.98 to 0.27 mg·g^-1 upon increasing the pH from 8.5 to 11.0, whereas the adsorption of TPP on goethite hardly changed with increasing electrolyte concentration. The results of analysis of the kinetic and isothermal models showed that the adsorption was more in accord with the pseudo second-order equation and Freundlich model. The adsorption capacity decreased obviously regardless of the order of addition of TPP, HA, and goethite. Subsequent addition of FA led to a large increase in the adsorption capacity, which might be attributed to the adsorption ability of FA. According to the predictions of the kinetic and isothermal models and the spectroscopic evidence (X-ray diffraction (XRD), Fourier Transform infrared spectroscopy (FT-IR), and scanning electron microscope (SEM)), the adsorption mechanism may be mainly based on surface complexation and physical adsorption.

• 원예과학기술지
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• 제30권5호
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• pp.596-602
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• 2012

Infestations of Aphis gossypii per leaf in greenhouse cultivation of cucumbers were investigated to develop binomial sampling plans. An empirical $P_T-m$ model, $ln(m)={\alpha}+{\beta}ln[-ln(1-P_T)]$, was used to evaluate relationship between the proportion of infested leaves with ${\leq}$ T aphids per leaf ($P_T$) and mean aphid density (m). Tally thresholds (T) were set to 1, 3, 5, 7, and 9 aphids per leaf to find appropriate T in greenhouse cultivation of cucumbers. Increasing sample size had little effect on the precision of the binomial sampling plan. However, the precision increased with tally threshold. The binomial model with T = 5 provided appropriate predictions of the mean densities of A. gossypii in the greenhouse cultivation of cucumbers. Using a binomial model with T = 5 (sample size = 200), a wide range of densities (1.2 - 222.8 aphids per leaf) could be estimated with precision levels of 0.346 - 0.380 for $P_T$ values between 0.15 and 0.96. Binomial models were validated at T = 5 and 7 using 12 independent data sets. Both binomial models were robust and adequately described aphid densities; most of the independent sampling data fell within 95% confidence intervals around the prediction model.

• Nuclear Engineering and Technology
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• 제51권5호
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• pp.1355-1364
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• 2019

A recently published nuclear forensics methodology for source discrimination of separated weapons-grade plutonium utilizes intra-element isotope ratios and a maximum likelihood formulation to identify the most likely source reactor-type, fuel burnup and time since irradiation of unknown material. Sensitivity studies performed here on the effects of random measurement error and the uncertainty in intra-element isotope ratio values show that different intra-element isotope ratios have disproportionate contributions to the determination of the reactor parameters. The methodology is robust to individual errors in measured intra-element isotope ratio values and even more so for uniform systematic errors due to competing effects on the predictions from the selected intra-element isotope ratios suite. For a unique sample-model pair, simulation uncertainties of up to 28% are acceptable without impeding successful source-reactor discrimination. However, for a generic sample with multiple plausible sources within the reactor library, uncertainties of 7% or less may be required. The results confirm the critical role of accurate reactor core physics, fuel burnup simulations and experimental measurements in the proposed methodology where increased simulation uncertainty is found to significantly affect the capability to discriminate between the reactors in the library.

• Korean Journal of Radiology
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• 제24권11호
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• pp.1151-1163
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• 2023

Objective: To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model. Materials and Methods: A convolutional neural network was trained to predict age according to the bone development shown on a hand radiograph (bone age) using 21036 hand radiographs of Korean children and adolescents without known bone development-affecting diseases/conditions obtained between 1998 and 2019 (median age [interquartile range {IQR}], 9 [7-12] years; male:female, 11794:9242) and their chronological ages as labels (Korean model). We constructed 2 separate external datasets consisting of Korean children and adolescents with healthy bone development (Institution 1: n = 343; median age [IQR], 10 [4-15] years; male: female, 183:160; Institution 2: n = 321; median age [IQR], 9 [5-14] years; male: female, 164:157) to test the model performance. The mean absolute error (MAE), root mean square error (RMSE), and proportions of bone age predictions within 6, 12, 18, and 24 months of the reference age (chronological age) were compared between the Korean model and a commercial model (VUNO Med-BoneAge version 1.1; VUNO) trained with Greulich-Pyle-based age as the label (GP-based model). Results: Compared with the GP-based model, the Korean model showed a lower RMSE (11.2 vs. 13.8 months; P = 0.004) and MAE (8.2 vs. 10.5 months; P = 0.002), a higher proportion of bone age predictions within 18 months of chronological age (88.3% vs. 82.2%; P = 0.031) for Institution 1, and a lower MAE (9.5 vs. 11.0 months; P = 0.022) and higher proportion of bone age predictions within 6 months (44.5% vs. 36.4%; P = 0.044) for Institution 2. Conclusion: The Korean model trained using the chronological ages of Korean children and adolescents without known bone development-affecting diseases/conditions as labels performed better in bone age assessment than the GP-based model in the Korean pediatric population. Further validation is required to confirm its accuracy.

• Wind and Structures
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• 제18권4호
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• pp.423-441
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• 2014

The high frequency base balance (HFBB) technique is a convenient and relatively fast wind tunnel testing technique for predicting wind-induced forces for tall building design. While modern tall building design has seen a number architecturally remarkable buildings constructed recently, the characteristics of those buildings are significantly different to those that were common when the HFBB technique was originally developed. In particular, the prediction of generalized forces for buildings with 3-dimensional mode shapes has a number of inherent uncertainties and challenges that need to be overcome to accurately predict building loads and responses. As an alternative to the more conventional application of general mode shape correction factors, an analysis methodology, referred to as the linear-mode-shape (LMS) method, has been recently developed to allow better estimates of the generalized forces by establishing a new set of centers at which the translational mode shapes are linear. The LMS method was initially evaluated and compared with the methods using mode shape correction factors for a rectangular building, which was wind tunnel tested in isolation in an open terrain for five incident wind angles at $22.5^{\circ}$ increments from $0^{\circ}$ to $90^{\circ}$. The results demonstrated that the LMS method provides more accurate predictions of the wind-induced loads and building responses than the application of mode shape correction factors. The LMS method was subsequently applied to a tall building project in Hong Kong. The building considered in the current study is located in a heavily developed business district and surrounded by tall buildings and mixed terrain. The HFBB results validated the versatility of the LMS method for the structural design of an actual tall building subjected to the varied wind characteristics caused by the surroundings. In comparison, the application of mode shape correction factors in the HFBB analysis did not directly take into account the influence of the site specific characteristics on the actual wind loads, hence their estimates of the building responses have a higher variability.

• Earthquakes and Structures
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• 제19권2호
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• pp.129-144
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• 2020

In this study, the idea of damping force linearly proportional to horizontal isolation displacement is implemented into sloped rolling-type bearings in order to meet different seismic performance goals. In addition to experimentally demonstrating its practical feasibility, the previously developed analytical model is further modified to be capable of accurately predicting its hysteretic behavior. The numerical predictions by using the modified analytical model present a good match of the shaking table test results. Afterward, several sloped rolling-type bearings designed with linearly variable damping force are numerically compared with a bearing designed with conventional constant damping force. The initial friction damping force adopted in the former is designed to be smaller than the constant one adopted in the latter. The numerical comparison results indicate that when the horizontal isolation displacement does not exceed the designed turning point (or practically when subjected to minor or frequent earthquakes that seldom have a great displacement demand for seismic isolation), the linearly variable damping force design can exhibit a better acceleration control performance than the constant damping force design. In addition, the former, in general, advantages the re-centering performance over the latter. However, the maximum horizontal displacement response of the linearly variable damping force design, in general, is larger than that of the constant damping force design. It is particularly true when undergoing a horizontal isolation displacement response smaller than the designed turning point and designing a smaller value of initial friction damping force.

• Geomechanics and Engineering
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• 제18권3호
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• pp.299-313
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• 2019

This research investigated the nonlinear compressibility, permeability, the yielding due to structural degradation and their effects on consolidation behavior of structured soft soils. Based on oedometer and hydraulic conductivity test results of natural and reconstituted soft clays, linear log (1+e) ~ $log\;{\sigma}^{\prime}$ and log (1+e) ~ $log\;k_v$ relationships were developed to capture the variations in compressibility and permeability, and the yield stress ratio (YSR) was introduced to characterize the soil structure of natural soft clay. Semi-analytical solutions for one-dimensional consolidation of soft clay under time-dependent loading incorporating the effects of soil nonlinearity and soil structure were proposed. The semi-analytical solutions were verified against field measurements of a well-documented test embankment and they can give better accuracy in prediction of excess pore pressure compared to the predictions using the existing analytical solutions. Additionally, parametric studies were conducted to analyze the effects of YSR, compression index (${\lambda}_r$ and ${\lambda}_c$), and permeability index (${\eta}_k$) on the consolidation behavior of structured soft clays. The magnitude of the difference between degree of consolidation based on excess pore pressure ($U_p$) and that based on strain ($U_s$) depends on YSR. The parameter ${\lambda}_c/{\eta}_k$ plays a significant role in predicting consolidation behavior.

• Nuclear Engineering and Technology
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• 제52권12호
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• pp.2709-2716
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• 2020

Compositions of large nuclear cores (e.g. boiling water reactors) are highly heterogeneous in terms of fuel composition, control rod insertions and flow regimes. For this reason, they usually lack high order of symmetry (e.g. 1/4, 1/8) making it difficult to estimate their neutronic parameters for large spaces of possible loading patterns. A detailed hyperparameter optimization technique (a combination of manual and Gaussian process search) is used to train and optimize deep neural networks for the prediction of three neutronic parameters for the Ringhals-1 BWR unit: power peaking factors (PPF), control rod bank level, and cycle length. Simulation data is generated based on half-symmetry using PARCS core simulator by shuffling a total of 196 assemblies. The results demonstrate a promising performance by the deep networks as acceptable mean absolute error values are found for the global maximum PPF (~0.2) and for the radially and axially averaged PPF (~0.05). The mean difference between targets and predictions for the control rod level is about 5% insertion depth. Lastly, cycle length labels are predicted with 82% accuracy. The results also demonstrate that 10,000 samples are adequate to capture about 80% of the high-dimensional space, with minor improvements found for larger number of samples. The promising findings of this work prove the ability of deep neural networks to resolve high dimensionality issues of large cores in the nuclear area.

• Ecology and Resilient Infrastructure
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• 제5권1호
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• pp.25-34
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• 2018

본 연구에서는 만경강에서의 장기하상변동 모의를 실시하고 하상변동 이력을 분석하였다. 연구 대상 지역은 만경강의 중 하류 25 km 구간이다. 장기하상변동 모의를 위하여 HEC-RAS 프로그램을 사용하였으며 조도계수를 이용하여 모형을 보정하였다. 1986년부터 1993년까지의 기간과 1993년부터 2005년까지의 기간에 대하여 하상변동 모의를 수행하였으며, 실측된 하상고와의 비교분석을 실시하였다. MPM, Toffaleti, MPM-Toffaleti, Yang 공식의 네가지 유사이송 공식의 적용성을 평가하였다. 1986년부터 1993년까지의 기간에 대한 모의 결과, 네가지 공식 모두 실측치를 적절하게 모의하지 못하였다. 이는 모의구간 상류에서의 준설이 발생한 것으로 인한 결과이며 이후 기간에서 상류에서 퇴적이 활발이 진행되게 되는 결과를 초래하였다. 1993년 부터 2005년까지의 장기하상변동 모의는 MPM-Toffaleti의 공식이 모의를 적절히 수행해 냄을 확인하였다.

• 한국환경복원기술학회지
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• 제26권4호
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• pp.17-34
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• 2023

Camera trapping has been used as a non-invasive survey method that minimizes anthropogenic disturbance to ecosystems. Nevertheless, it is labor-intensive and time-consuming, requiring researchers to quantify species and populations. In this study, we aimed to improve the preprocessing of camera trapping data by utilizing an object detection algorithm. Wildlife monitoring using unmanned sensor cameras was conducted in a forested urban forest and a green space on a university campus in Cheonan City, Chungcheongnam-do, Korea. The collected camera trapping data were classified by a researcher to identify the occurrence of species. The data was then used to test the performance of the YOLO-X object detection algorithm for wildlife detection. The camera trapping resulted in 10,500 images of the urban forest and 51,974 images of green spaces on campus. Out of the total 62,474 images, 52,993 images (84.82%) were found to be false positives, while 9,481 images (15.18%) were found to contain wildlife. As a result of wildlife monitoring, 19 species of birds, 5 species of mammals, and 1 species of reptile were observed within the study area. In addition, there were statistically significant differences in the frequency of occurrence of the following species according to the type of urban greenery: Parus varius(t = -3.035, p < 0.01), Parus major(t = 2.112, p < 0.05), Passer montanus(t = 2.112, p < 0.05), Paradoxornis webbianus(t = 2.112, p < 0.05), Turdus hortulorum(t = -4.026, p < 0.001), and Sitta europaea(t = -2.189, p < 0.05). The detection performance of the YOLO-X model for wildlife occurrence was analyzed, and it successfully classified 94.2% of the camera trapping data. In particular, the number of true positive predictions was 7,809 images and the number of false negative predictions was 51,044 images. In this study, the object detection algorithm YOLO-X model was used to detect the presence of wildlife in the camera trapping data. In this study, the YOLO-X model was used with a filter activated to detect 10 specific animal taxa out of the 80 classes trained on the COCO dataset, without any additional training. In future studies, it is necessary to create and apply training data for key occurrence species to make the model suitable for wildlife monitoring.