• Geomechanics and Engineering
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• v.36 no.2
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• pp.111-119
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• 2024

In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R²) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.

• Journal of the Korean Magnetics Society
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• v.14 no.6
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• pp.236-239
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• 2004

We studied the specular spin valve (SSV) having the spin filter layer (SFL) in contact with the ultrathin free layer composed of Ta3/NiFe2/IrMn7/CoFel/(NOLl)/CoFe2/Cu1.8/CoFe( $t_{F}$)/Cu( $t_{SF}$ )/(NOL2)/Ta3.5 (in nm) by the magnetron sputtering system. For this antiferromagnetic I $r_{22}$M $n_{78}$-pinned spin filter specular spin valve (SFSSV) films, an optimal magnetoresistance (MR) ratio of 11.9% was obtained when both the free layer thickness ( $t_{F}$) and the SFL thickness ( $t_{SF}$ ) were 1.5 nm, and the MR ratio higher than 11% was maintained even when the $t_{F}$ was reduced to 1.0 nm. It was due to increase of specular electron by the nano-oxide layer (NOL) and of current shunting through the SFL. Moreover, the interlayer coupling field ( $H_{int}$) between free layer and pinned layer could be explained by considering the RKKY and magnetostatic coupling. The coercivity of the free layer ( $H_{cf}$ ) was significantly reduced as compared to the traditional spin valve (TSV), and was remained as low as 4 Oe when the $t_{F}$ varied from 1 nm to 4 urn. It was found that the SFL made it possible to reduce the free layer thickness and enhance the MR ratio without degrading the soft magnetic property of the free layer.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.12
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• pp.4815-4821
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• 2014

Background: This study aimed to examine the relationship between respiratory health of Malaysian adolescents with secondhand smoke (SHS) exposure and smoke-free legislation (SFL) implementation. Materials and Methods: A total of 898 students from 21 schools across comprehensive- and partial-SFL states were recruited. SHS exposures and respiratory symptoms were assessed via questionnaire. Prenatal and postnatal SHS exposure information was obtained from parental-completed questionnaire. Results: The prevalence of respiratory symptoms was: 11.9% ever wheeze, 5.6% current wheeze, 22.3% exercise-induced wheeze, 12.4% nocturnal cough, and 13.1% self-reported asthma. SHS exposure was most frequently reported in restaurants. Hierarchical logistic regression indicates living in a comprehensive-SFL state was not associated with a lower risk of reporting asthma symptoms. SHS exposure in public transport was linked to increased risk for wheeze (Adjusted Odds Ratio (AOR) 16.6; 95%confidence interval (CI), 2.69-101.7) and current wheezing (AOR 24.6; 95%CI, 3.53-171.8). Conclusions: Adolescents continue to be exposed to SHS in a range of public venues in both comprehensive- and partial-SFL states. Respiratory symptoms are common among those reporting SHS exposure on public transportation. Non-compliance with SFL appears to be frequent in many venues across Malaysia and enforcement should be given priority in order to reduce exposure.

• Journal of the Korea Society of Computer and Information
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• v.22 no.4
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• pp.25-32
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• 2017

Recently, the use of NAND flash memory is being increased as a secondary device to displace conventional magnetic disk. NAND flash memory, as one among non-volatile memories, has many advantages such as low power, high reliability, low access latency, and so on. However, NAND flash memory has disadvantages such as erase-before-write, unbalanced operation speed, and limited P/E cycles, unlike conventional magnetic disk. To solve these problems, NAND flash memory mainly adopted FTL (Flash Translation Layer). In particular, garbage collection technique in FTL tried to improve the system lifetime. However, previous garbage collection techniques have a sensitive property of the system lifetime according to write pattern. To solve this problem, we propose BSGC (Balanced Selection-based Garbage Collection) technique. BSGC efficiently selects a victim block using all intervals from the past information to the current information. In this work, SFL (Search First linked List), as the proposed block allocation policy, prolongs the system lifetime additionally. In our experiments, SFL and BSGC prolonged the system lifetime about 12.85% on average and reduced page migrations about 22.12% on average. Moreover, SFL and BSGC reduced the average response time of 16.88% on average.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.197-211
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• 2024

This research studies the effect of geotechnical factors on EPB-TBM performance parameters. The modeling was performed using simple and multivariate linear regression methods, artificial neural networks (ANNs), and Sugeno fuzzy logic (SFL) algorithm. In ANN, 80% of the data were randomly allocated to training and 20% to network testing. Meanwhile, in the SFL algorithm, 75% of the data were used for training and 25% for testing. The coefficient of determination (R²) obtained between the observed and estimated values in this model for the thrust force and cutterhead torque was 0.19 and 0.52, respectively. The results showed that the SFL outperformed the other models in predicting the target parameters. In this method, the R² obtained between observed and predicted values for thrust force and cutterhead torque is 0.73 and 0.63, respectively. The sensitivity analysis results show that the internal friction angle (φ) and standard penetration number (SPT) have the greatest impact on thrust force. Also, earth pressure and overburden thickness have the highest effect on cutterhead torque.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1477-1488
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• 2014

Prevalent construction of impermeable pavements in urban areas causes diverse water-related environmental issues, such as lowering ground water levels and shortage of water supply for the living. In order to resolve such problems, a rainwater reservoir can be an effective and useful solution. The rainwater reservoir facilitates the hydrologic cycle in urban areas by temporarily retaining precipitation-runoff within a shallow subsurface layer for later use in a dry season. However, in order to use the stored water of precipitation-runoff, non-point source pollutants mostly retained in initial rainfall should be removed before being stored in the reservoir. Therefore, the purification system to filter out the non-point source pollutants is essential for the rainwater reservoir. The conventional soil filtration technology is well known to be able to capture non-point source pollutants in a economical and efficient way. This study adopted a sand filter layer (SFL) as a non-point source pollutant removal system in the rainwater reservoir, and conducted a series of lab-scale chamber tests and field tests to evaluate the pollutant removal efficiency and applicability of SFL. During the laboratory chamber experiments, three types of SFL with the different grain size characteristics were compared in the chamber with a dimension of $20cm{\times}30cm{\times}60cm$. To evaluate performance of the reservoir systems, the concentration of the polluted water in terms of TSS (Total Suspended Solids) and COD (Chemical Oxygen Demand) were measured and compared. In addition, a reduction in hydraulic conductivity of SFL due to pollutant clogging was indirectly estimated. The optimum SFL selected through the laboratory chamber experiments was verified on the in-situ rainwater reservoir for field applicability.

• Computers and Concrete
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• v.21 no.1
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• pp.103-110
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• 2018

This study introduces the supervised committee fuzzy model as a hybrid fuzzy model to predict compressive strength (CS) of geopolymers prepared from alumina-silica products. For this purpose, more than 50 experimental data that evaluated the effect of $Al_2O_3/SiO_2$, $Na_2O/Al_2O_3$, $Na_2O/H_2O$ and Na/[Na+K] on (CS) of geopolymers were collected from the literature. Then, three different Fuzzy Logic (FL) models (Sugeno fuzzy logic (SFL), Mamdani fuzzy logic (MFL), and Larsen fuzzy logic (LFL)) were adopted to overcome the inherent uncertainty of geochemical parameters and to predict CS. After validating the model, it was found that the SFL model is superior to MFL and LFL models, but each of the FL models has advantages to predict CS. Therefore, to achieve the optimal performance, the supervised committee fuzzy logic (SCFL) model was developed as a hybrid method to combine the benefits of individual FL models. The SCFL employs an artificial neural network (ANN) model to re-predict the CS of three FL model predictions. The results also show significant fitting improvement in comparison with individual FL models.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1028-1029
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• 2015

본 연구에서는 대전류 구간에서의 아크해석 결과를 이용하여 SLF 차단성능을 예측하기 위하여 과도회복전압 상승률에 따라 전류영점 후 수~수백 마이크로초 동안 $SF_6$ 아크현상 이력과 영점후전류를 계산하여 대전류 구간 마지막 시점에서의 10,000K 이하의 가느다란 잔류아크가 완전히 소호될지 아니면 아크가 다시 재발호될지 판단하였다.

• International Journal of Industrial Entomology and Biomaterials
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• v.23 no.1
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• pp.183-186
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• 2011

The various molecular weight (MW) regenerated silk fibroins were prepared with different dissolution condition and the effect of MW on the gelation behavior of regenerated aqueous silk fibroin (SF) solution was investigated. The result of gelation time measurement indicated that the gelation of SF aqueous solution was accelerated by the increase of MW and SF concentration. When formic acid was added in SF aqueous solution, the gelation time of SFL and SFC30 aqueous solution showed a significant decreaseat 0.03% formic acid addition. In case of the lowest MW sample, SFC180, SF molecules became aggregated and precipitated without gelation after 28 days storage time. These findings indicate that MW control of SF can be utilized to control the gelation time of SF aqueous solution.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.297-300
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• 2017

본 연구는 기술수용모델(Technology Acceptance Model)을 기반으로 <클림트 인사이드(2017)>전시에서 사용된 <스토클렛 저택의 장식벽화(Stoclet Frieze)> VR 앱에 대한 인지된 유용성(이하 PU)과 인지된 이용용이성(이하 PEOU)의 평가에 초점을 맞추었다. VR 앱의 학습적합성(SFL)이 감상적합성(SFA)보다 높게 평가된 PU의 경우, 학습유용성(UFL)과 감상유용성(UFA)의 모든 요인이 만족도(DOS)에 긍정적인 영향을 미침으로써, 전시환경에서의 VR 앱의 학습에 대한 내적 동기 부여 및 감상 지원에 대한 잠재력이 확인되었다. 또한 PEOU의 모든 요인들은 DOS뿐만 아니라 DOI와도 유의미한 상관관계를 가졌다. 본 연구를 통해 TAM의 PU와 PEOU의 ATUA(DOS 및 DOI) 및 BITUA(ITRA(1) 및 ITRA(2))에 대한 영향력이 검증됨에 따라, 두 변수는 사용자의 VR 앱에 대한 기술 수용에 대한 예측을 가능케 했으며, 결론적으로 예술작품 원작을 재매개한 VR 앱에 대한 평가모델로써 TAM의 적합성이 입증되었다.