• Computers and Concrete
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• v.32 no.2
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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.

• Steel and Composite Structures
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• v.45 no.1
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• pp.67-82
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• 2022

In this paper, buckling and free vibration of imperfect, functionally graded beams, including porosities, are investigated, using a higher order shear strain theory. Due to defects during the manufacturing process, micro porosities may appear in the material, hence the appearance of this imperfection in the structure. The material properties of the beams are assumed to vary regularly, with power and sigmoid law, in the direction of thickness. A novel porosity distribution affecting the functionally graded volume fraction is presented. For the compact formulation used for cementite-based materials and already used in P-FGM, we have adapted it for the distribution of S-FGM. The equations of motion in the FG beam are derived using Hamilton's principle. The boundary conditions for beam FG are assumed to be simply supported. Navier's solution is used to obtain the closed form solutions of the FG beam. The numerical results of this work are compared with those of other published research to verify accuracy and reliability. The comparisons of different shear shape functions, the influence of porosity, thickness and inhomogeneity parameters on buckling and free vibration of the FG beam are all discussed. It is established that the present work is more precise than certain theories developed previously.

• Advances in nano research
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• v.16 no.5
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• pp.509-519
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• 2024

In this study, the static analysis of carbon nanotube-reinforced composites (CNTRC) beams resting on a Winkler-Pasternak elastic foundation is presented. The developed theories account for higher-order variation of transverse shear strain through the depth of the beam and satisfy the stress-free boundary conditions on the top and bottom surfaces of the beam. To study the effect of carbon nanotubes distribution in functionally graded (FG-CNT), we introduce in the equation of CNT volume fraction a new exponent equation. The SWCNTs are assumed to be aligned and distributed in the polymeric matrix with different patterns of reinforcement. The rule of mixture is used to describe the material properties of the CNTRC beams. The governing equations were derived by employing Hamilton's principle. The models presented in this work are numerically provided to verify the accuracy of the present theory. The analytical solutions are presented, and the obtained results are compared with the existing solutions to verify the validity of the developed theories. Many parameters are investigated, such as the Pasternak shear modulus parameter, the Winkler modulus parameter, the volume fraction, and the order of the exponent in the volume fraction equation. New results obtained from bending and stresses are presented and discussed in detail. From the obtained results, it became clear the influence of the exponential CNTs distribution and Winkler-Pasternak model improved the mechanical properties of the CNTRC beams.

• Hip & pelvis
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• v.35 no.3
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• pp.175-182
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• 2023

Purpose: This study aims to compare patients in whom fixation failure occurred via cut-out (CO) or cut-through (CT) in order to determine patient factors and radiographic parameters that may be predictive of each mechanism. Materials and Methods: This retrospective cohort study includes 18 patients with intertrochanteric (IT) hip fractures (AO/OTA classification 31A1.3) who underwent treatment using a single lag screw design intramedullary nail in whom fixation failure occurred within one year. All patients were reviewed for demographics and radiographic parameters including tip-to-apex distance (TAD), posteromedial calcar continuity, neck-shaft angle, lateral wall thickness, and others. Patients were grouped into cohorts based on the mechanism of failure, either lag screw CO or CT, and a comparison was performed. Results: No differences in demographics, injury details, fracture classifications, or radiographic parameters were observed between CO/CT cohorts. Of note, a similar rate of post-reduction TAD>25 mm (P=0.936) was observed between groups. A higher rate of DEXA (dual energy X-ray absorptiometry) confirmed osteoporosis (25.0% vs. 60.0%) was observed in the CT group, but without significance. Conclusion: The mechanism of CT failure during intramedullary nail fixation of an IT fracture did not show an association with clinical data including patient demographics, reduction accuracy, or radiographic parameters. As reported in previous biomechanical studies, the main predictive factor for patients in whom early failure might occur via the CT effect mechanism may be related to bone quality; however, conduct of larger studies will be required in order to determine whether there is a difference in bone quality.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.233-244
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• 2014

Precise Point Positioning (PPP) is an increasingly recognized precisely the GPS/GNSS positioning technique. In order to improve the accuracy of PPP, the error sources in PPP measurements should be reduced as much as possible and the ambiguities should be correctly resolved. The correct ambiguity resolution requires a careful control of residual errors that are normally categorized into random and systematic errors. To understand effects from two categorized errors on the PPP ambiguity resolution, those two GPS datasets are simulated by generating in locations in South Korea (denoted as SUWN) and Hong Kong (PolyU). Both simulation cases are studied for each dataset; the first case is that all the satellites are affected by systematic and random errors, and the second case is that only a few satellites are affected. In the first case with random errors only, when the magnitude of random errors is increased, L1 ambiguities have a much higher chance to be incorrectly fixed. However, the size of ambiguity error is not exactly proportional to the magnitude of random error. Satellite geometry has more impacts on the L1 ambiguity resolution than the magnitude of random errors. In the first case when all the satellites have both random and systematic errors, the accuracy of fixed ambiguities is considerably affected by the systematic error. A pseudorange systematic error of 5 cm is the much more detrimental to ambiguity resolutions than carrier phase systematic error of 2 mm. In the $2^{nd}$ case when only a portion of satellites have systematic and random errors, the L1 ambiguity resolution in PPP can be still corrected. The number of allowable satellites varies from stations to stations, depending on the geometry of satellites. Through extensive simulation tests under different schemes, this paper sheds light on how the PPP ambiguity resolution (more precisely L1 ambiguity resolution) is affected by the characteristics of the residual errors in PPP observations. The numerical examples recall the PPP data analysts that how accurate the error correction models must achieve in order to get all the ambiguities resolved correctly.

• Korean Journal of Food Science and Technology
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• v.24 no.5
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• pp.408-413
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• 1992

This study was conducted to determine the effect of the homogenizing grade of sample on absorbance of near infrared reflectance spectrophotometer with which chemical compositions of food were rapidly and effectively analyzed. By the mathematical treatment of absorbance values standard error of prediction was reduced as follows. 1. The absorbance values of various samples ground for the same periods of time were calibrated before or after treatment with first or second derivative in an attempt to accurately predict the components of samples ground for the different periods of time. The standard error of prediction for moisture content were 1.478%, 0.658% and 0.580%, respectively, those for fat content 0.949%, 0.637% and 0.527%, respectively, and those for protein content 0.514%, 0.493% and 0.394%, respectively. Calibration of absorbance values after second derivative treatment showed the highest accuracy in predicting sample components. 2. The absorbance values of various samples ground for the different periods of time were calibrated before or after treatment with first or second derivative in order to accurately predict the components of samples ground for the different periods of time. The standard error of prediction for moisture content were 1.026%, 0.589% and 0.568%, respectively, and those for protein content 0.860%, 0.557% and 0.399%, respectively. The standard error of prediction were lower in the order of calibrations before and after first and second derivative treatments. As a result, calibration of absorbance values after second derivative treatment showed higher accuracy regardless of grinding time of samples.

• Phonetics and Speech Sciences
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• v.16 no.3
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• pp.39-48
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• 2024

Reading fluency refers to the ability to read sentences or paragraphs accurately, quickly, and with appropriate prosodic expression. Most reading fluency assessments exclude expressive ability because it is difficult to objectively measure. Therefore, in this study, we examined all elements of reading fluency by analyzing prosodic characteristics of reading scenario texts to maximize expressive reading. The subjects were 30 male students in the first and second grades of middle school (15 normal and 15 poor readers). To analyze the accuracy aspect, error types at the syllable level were analyzed for each group, and related acoustic variables were measured and examined in terms of prosodic aspects. The reading accuracy analysis showed that the poor reading group had a higher error rate than the normal. In terms of error types, the normal group showed the order of 'substitution>omission>correction>insertion>repetition', whereas the poor reading group was in the order of 'correction>substitution>repetition/insertion>omission'. For the speech tempo, the dyslexic students were slower than the typical students for all sentence types. The prosodic variables also showed a high frequency of accentual phrases (AP) and intonation phrases (IP) in sentences along with a wide intensity range.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.33-42
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• 2020

There has been difficulties in identifying objects by relying on the naked eye in various surveillance systems. There is a growing need for automated surveillance systems to replace soldiers in the field of military surveillance operations. Even though the object detection technology is developing rapidly in the civilian domain, but the research applied to the military is insufficient due to a lack of data and interest. Thus, in this paper, we applied one of deep learning algorithms, Convolutional Neural Network-based binary classification to develop an autonomous identification model of both friend and foe helicopters (AH-64, Mi-17) among the military weapon systems, and evaluated the model performance by considering accuracy, precision, recall and F-measure. As the result, the identification model demonstrates 97.8%, 97.3%, 98.5%, and 97.8 for accuracy, precision, recall and F-measure, respectively. In addition, we analyzed the feature map on convolution layers of the identification model in order to check which area of imagery is highly weighted. In general, rotary shaft of rotating wing, wheels, and air-intake on both of ally and foe helicopters played a major role in the performance of the identification model. This is the first study to attempt to classify images of helicopters among military weapons systems using CNN, and the model proposed in this study shows higher accuracy than the existing classification model for other weapons systems.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.409-417
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• 2016

The purpose of this study was to demonstrate the effect on the degree of fatigue and accuracy of cardiopulmonary resuscitation according to the different time delays (3 minutes, 4 minutes). Carrying out repeated measures of variance (repeated ANOVA), we have shown that time effect (F = 7.835, p <.01) and group effect (F = 8.695, p<.01) and the interaction effect between time and group (F = 12.582, p<.001) were all statistically significant. It means, in the test of the main effect of group and time (3 minutes, 4 minutes) using the Bonferroni method, it turned out that the amount of lactic acid of the experimental group was larger than that of the control group (p<.01), and there was no difference until 3 minutes, but the difference of the amount of lactic acid was shown between before the experiment and after 4 minutes, and between 3 minutes and 4 minutes (p <.05), respectively. Then, in the result of the corresponding sample t-test, for comparing the according to the measurement time, the accuracy after 3 minutes became higher than the case of 4 minutes (t = 4.584, p <.001). Therefore, before 119 arrives performing cardiopulmonary resuscitation for emergency, rescuers need to perform cardiopulmonary resuscitation alternating with others before 3 minutes.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.21-35
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• 2020

Vegetation information is a very important factor used in various fields such as urban planning, landscaping, water resources, and the environment. Vegetation varies according to canopy density or chlorophyll content, but vegetation vitality is not considered when classifying vegetation areas in previous studies. In this study, in order to satisfy various applied studies, a study was conducted to set a threshold value of vegetation index considering vegetation vitality. First, an eBee fixed-wing drone was equipped with a multi-spectral camera to construct optical and near-infrared orthomosaic images. Then, GIS calculation was performed for each orthomosaic image to calculate the NDVI, GNDVI, SAVI, and MSAVI vegetation index. In addition, the vegetation position of the target site was investigated through VRS survey, and the accuracy of each vegetation index was evaluated using vegetation vitality. As a result, the scenario in which the vegetation vitality point was selected as the vegetation area was higher in the classification accuracy of the vegetation index than the scenario in which the vegetation vitality point was slightly insufficient. In addition, the Kappa coefficient for each vegetation index calculated by overlapping with each site survey point was used to select the best threshold value of vegetation index for classifying vegetation by scenario. Therefore, the evaluation of vegetation index accuracy considering the vegetation vitality suggested in this study is expected to provide useful information for decision-making support in various business fields such as city planning in the future.