• Composites Research
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• v.36 no.1
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• pp.59-67
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• 2023

Damage caused by impact on a vehicle composed of CFRP(carbon fiber reinforced plastic) composite to reduce weight in the aerospace industries is related to the safety of passengers. Therefore, it is important to understand the damage behavior of materials that is invisible in impact situations, and research through the FEM(finite element model) is needed to simulate this. In this study, FEM suitable for predicting damage behavior was constructed for impact analysis of unidirectional laminated composite. The calibration parameters of the MAT_54 Enhanced Composite Damage material model in LS-DYNA were acquired by inverse estimation through ANN(artificial neural network) model. The reliability was verified by comparing the result of experiment with the results of the ANN model for the obtained parameter. It was confirmed that accuracy of FEM can be improved through optimization of calibration parameters.

• The Journal of Advanced Prosthodontics
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• v.15 no.6
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• pp.315-332
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• 2023

PURPOSE. This study aimed to investigate whether the accuracy of intraoral scanners is influenced by different scanning strategies in an in vitro setting, through a systematic review and meta-analysis. MATERIALS AND METHODS. This review was conducted in accordance with the PRISMA 2020 standard. The following PICOS approach was used: population, tooth impressions; intervention, the use of intraoral scanners with scanning strategies different from the manufacturer's instructions; control, the use of intraoral scanners following the manufacturers' requirements; outcome, accuracy of intraoral scanners; type of studies, in vitro. A comprehensive literature search was conducted across various databases including Embase, SciELO, PubMed, Scopus, and Web of Science. The inclusion criteria were based on in vitro studies that reported the accuracy of digital impressions using intraoral scanners. Analysis was performed using Review Manager software (version 5.3.5; Cochrane Collaboration, Copenhagen, Denmark). Global comparisons were made using a standardized mean difference based on random-effect models, with a significance level of α = 0.05. RESULTS. The meta-analysis included 15 articles. Digital impression accuracy significantly improved under dry conditions (P < 0.001). Moreover, trueness and precision were enhanced when artificial landmarks were used (P ≤ 0.02) and when an S-shaped pattern was followed (P ≤ 0.01). However, the type of light used did not have a significant impact on the accuracy of the digital intraoral scanners (P ≥ 0.16). CONCLUSION. The accuracy of digital intraoral scanners can be enhanced by employing scanning processes using artificial landmarks and digital impressions under dry conditions.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.340-347
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• 2008

Dipstick urinalysis is used as a routine test for a screening test of UTI (urinary tract infection) in primary practice because urine dipstick test is simple. The result of dipstick urinalysis brings medical professionals to make a microscopic examination and urine culture for exact UTI diagnosis, therefore it is emphasized on a role of screening test. The objective of this study was to the classification between UTI patients and normal subjects using hybrid neural network classifier with enhanced clustering performance in urine dipstick screening test. In order to propose a classifier, we made a hybrid neural network which combines with RBF layer, summation & normalization layer and L VQ artificial neural network layer. For the demonstration of proposed hybrid neural network, we compared proposed classifier with various artificial neural networks such as back-propagation, RBFNN and PNN method. As a result, classification performance of proposed classifier was able to classify 95.81% of the normal subjects and 83.87% of the UTI patients, total average 90.72% according to validation dataset. The proposed classifier confirms better performance than other classifiers. Therefore the application of such a proposed classifier expect to utilize telemedicine to classify between UTI patients and normal subjects in the future.

• Macromolecular Research
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• v.17 no.12
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• pp.1032-1038
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• 2009

A polypyrrole (PPy)/alumina composite filler prepared via in-situ polymerization of pyrrole on alumina particles was incorporated into $Nafion^{(R)}$ to improve the performance of ionic polymer-metal composite (IPMC) actuators. The IPMCs with the pristine PPy without alumina support did not show bending displacements superior to that of the bare Nafion-based IPMC, except at a high PPy content of 4 wt%. This result was attributed to the low redox efficiency of the PPy alone in the IPMC and may have also been related to the modulus of the IPMC. However, at the optimized filler contents, the cyclic displacement of the IPMCs bearing the PPy/alumina filler was 2.2 times larger than that of the bare Nafion-based IPMC under an applied AC potential of 3 Vat 1 Hz. Even under a low AC potential of 1.5 V at 1 Hz, the displacement of the PPy/alumina-based IPMCs was a viable level of performance for actuator applications and was 2.7 times higher than that of the conventional Nafion-based IPMC. The generated blocking force was also improved with the PPy/aiumina composite filler. The greatly enhanced performance and the low-voltage-operational characteristic of the IPMCs bearing the PPy/alumina filler were attributed to the synergic effects of the neighboring alumina moiety near the PPy moiety involving electrochemical redox reactions.

• Journal of Marine Bioscience and Biotechnology
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• v.6 no.2
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• pp.123-130
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• 2014

Three types of artificial microparticle diets were developed for rotifer (Brachionus plicatilis) enrichment. The efficacies of enrichment with the artificial diets were evaluated and compared to those with commercial enrichment diets on the growth and survival of flounder larvae. Total lipid content was highest in the rotifer enriched with oil capsule (40.5% in dry weight). The n-3 highly unsaturated fatty acid (n-3 HUFA) content was also highest in the rotifer fed with oil capsule (7.08% in dry weight). The flounder larvae fed on the rotifer enriched with oil capsule showed the highest growth compared to those fed on any other enriched rotifer (P<0.05). The survival ratio of flounder larvae fed on the rotifers enriched with oil capsule and emulsion oil were higher than those fed on any other enriched rotifer (P<0.05). From the feeding study, the growth and survival of flounder larvae were enhanced by feeding rotifer enriched with oil capsule compared to rotifer enriched with any other diets. The rotifer fed on oil capsule containing high contents of n-3 HUFA. Therefore, a significant relationship between the growth and survival of flounder larvae and the n-3 HUFA content of rotifer could be obtained.

• Journal of Sensor Science and Technology
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• v.24 no.6
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• pp.373-378
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• 2015

The structure of the human ear is divided into the outer ear, the middle ear, and the inner ear. The inner ear includes the cochlea that plays a very important role in hearing. Recently, the development of an artificial cochlear device for the hearing impaired with cochlear damage has been actively researched. Research has been carried out on the biomimetic piezoelectric thin film ABM (Artificial Basilar Membrane) in particular. In an effort to improve the frequency separation performance of the existing piezoelectric thin film ABM, this paper presents the design, fabrication, and characterization of the production and performance of a partially etched-type ABM material. $O_2$ plasma etching equipment was used to partially etch a piezoelectric thin film ABM to make it more flexible. The mechanical-behavior characterization of the manufactured partially etched-type ABM showed that the overall separation frequency range shifted to a lower frequency range more suitable for audible frequency bandwidths and it displayed an improved frequency separation performance. In addition, the maximum magnitude of the vibration displacement at the first local resonant frequency was enhanced by three times from 38 nm to 112 nm. It is expected that the newly designed, partially etched-type ABM will improve the issue of cross-talk between nearby electrodes and that the manufactured partially etched-type ABM will be utilized for next-generation ABM research.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.6
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• pp.419-423
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• 2015

The flowing caused by artificial upwelling structure occurs ascending water flowing and vortex of rear side. In this moment, plentiful nutrient in the bottom water moves to the surface of the water and makes those plankton and fishing ecology promoted so that the fishing productivity can be enhanced. In this study, the changes of the upwelling flowing is included in consideration of the conditions of stratification by using CFD. In the conclusion, the closer upwelling effect is from the artificial upwelling structure, the better effectiveness comes out. Regardless of the conditions of stratification, only the upwelling feature from the bottom to the surface was shown up. But considering the conditions of stratification, the repeated flowing feature between upwelling and downwelling was verified.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.161-166
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• 2021

Errors in the semiconductor process are generated by a change in the state of the equipment, and errors usually arise when the state of the equipment changes or when parts that make up the equipment have flaws. In this investigation, we anticipated that aging of the mass flow controller in the plasma enhanced chemical vapor deposition SiO2 thin film deposition method caused a minute flow rate shift. In seven cases, fourier transformation infrared film quality analysis of the deposited thin film was used to characterize normal and pathological processes. The plasma condition was monitored using optical emission spectrometry data as the flow rate changed during the procedure. Preprocessing was used to apply the collected OES data to the artificial immune system algorithm, which was then used to process diagnosis. Through comparisons between datasets, the learning algorithm compared classification accuracy and improved the method. It has been confirmed that data characterized as a normal process and abnormal processes with differing flow rates may be discriminated by themselves using the artificial immune system data mining method.

• 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.

• Design & Manufacturing
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• v.17 no.4
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.