• Membrane Journal
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• v.33 no.1
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• pp.34-45
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• 2023

Two computational intelligence techniques namely artificial neural networks (ANN) and support vector machine (SVM) are employed to model the permeate flux based on seven input variables including time, transmembrane pressure, rotating velocity, the pore diameter of the membrane, dynamic viscosity, concentration and density of the feed fluid. The best-fit model was selected through the trial-error method and the two statistical parameters including the coefficient of determination (R²) and the average absolute relative deviation (AARD) between the experimental and predicted data. The obtained results reveal that the optimized ANN model can predict the permeate flux with R² = 0.999 and AARD% = 2.245 versus the SVM model with R² = 0.996 and AARD% = 4.09. Thus, the ANN model is found to predict the permeate flux with high accuracy in comparison to the SVM approach.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.731-738
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• 2006

Facing congestion, people want to know traffic information about their routes, especially real-time link travel time (LTT). In this paper, as a sequel paper of the previous non-taxi based LTT generating study by Choi et al. (1998), taxi based GPS probes have been tried to produce LTT for urban arterials. Taxis in itself are good deployment mode of GPS probes although it by nature experiences boarding and alighting time noises which should be accounted. A heuristic real-time dynamic outlier filter algorithm for taxi GPS probe has been developed focusing on urban arterials. An actual traffic survey for dynamic link travel times has been conducted using license plate method for the test arterials of Seoul city transportation network. With the algorithm, it is estimated that 70% of outliers have been filtered and the relative error has been improved by 73.7%. The filtering algorithm developed here would be expected to be in use for other spatial sites with some calibration efforts. Some limitations and future research agenda have also been discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.263-269
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• 2006

An optimization model was developed for groundwater development and management in coastal areas. The optimization model consists of coastal groundwater flow model and optimization techniques. The objective of this work is to validate sharp-interface model which is one of major components of the optimization model. A laboratory experimental model is built to simulate freshwater lens, i.e., layer of freshwater floating on top of saltwater, phenomena. Experimental results for the position of fresh-saltwater sharp-interface and the salinity in well are compared with numerical results. Average ratio of relative error is estimated approximately between 2.91% and 4.39%. And the numerical results are in good agreement with the laboratory results of water quality in well in addition to the position of sharp-interface. Accordingly the evaluation of coastal groundwater flow using sharp-interface model can produce reasonable results.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.1-8
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• 2023

An Orthogonal Frequency Division Multiplexing (OFDM) based wireless communication system has drawn wide attention for its high transmission rate and high spectrum efficiency in not only radio but also Underwater Acoustic (UWA) applications. Because of the narrow sub-carrier spacing of OFDM, orthogonality between sub-carriers is easily affected by Doppler effect caused by the movement of transmitter or receiver. Previously, Doppler compensation signal processing algorithm for Desired propagation path was proposed. However, other Doppler shifts caused by delayed Undesired signal arriving from different directions cannot be perfectly compensated. Then Receiver Bit Error Rate (BER) is degraded by Inter-Carrier-Interference (ICI) caused in the case of Multi-path Doppler channel. To mitigate the ICI effect, a modified Delay and Doppler Profiler (mDDP), which estimates not only attenuation, relative delay and Doppler shift but also sampling clock shift of each multi-path component, is proposed. Based on the outputs of mDDP, an ICI canceling multi-tap equalizer is also proposed. Computer simulated performances of one-tap equalizer with the conventional Time domain linear interpolated Channel Transfer Function (CTF) estimator, multi-tap equalizer based on mDDP are compared. According to the simulation results, BER improvement has been observed. Especially, in the condition of 16QAM modulation, transmitting vessel speed of 6m/s, two-path multipath channel with direct path and ocean surface reflection path; more than one order of magnitude BER reduction has been observed at CNR=30dB.

• Safety and Health at Work
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• v.14 no.3
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• pp.332-339
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• 2023

Background: The aim of the study was to test the validity and reliability of the Perceived Future Decent Work Securement Scale for Turkish nursing students. Methods: A cross-sectional, methodological study design was used. The study was carried out at three nursing undergraduate programs in Turkey during the academic year of 2020-2021 with 336 senior nursing students. Language validity and content validity analyses were performed for the scale adaptation, followed by confirmatory factor analysis (CFA) for construct validity. The reliability of the scale was determined using the test-retest and Cronbach's alpha internal consistency coefficient. Results: The scale-content validity index score was 0.988. In CFA, all goodness-of-fit indices verified the acceptable fit of the model; its root mean square error of approximation was 0.076; the normed fit index was 0.909; the standardized mean square residual was 0.097; the relative fit index was 0.881; the goodness-of-fit index was 0.915; the adjusted goodness-of-fit index was 0.872 and χ²/df = 2.932. The overall reliability was α = 0.86. The item-total correlations of the scale were above the acceptable level, and the test-retest analysis had a high correlation. The access to healthcare (14.68, SD 3.53) obtained the highest average score, and the adequate compensation (8.52, SD 3.76) was the lowest rated by the senior nursing students. Conclusion: The Perceived Future Decent Work Securement Scale is a valid and reliable scale to assess nursing students' future decent work securement.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.

• Wind and Structures
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• v.37 no.4
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• pp.289-302
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• 2023

Insulating glass units (IGUs) have been widely used in buildings in recent years due to their superior thermal insulation performance. However, because of the panel reciprocating motion and fatigue deterioration of sealants under long-term wind loads, many IGUs have the problem of early failure of watertight properties in real usage. This study aimed to propose a statistical method for wind-induced deflection of IGU panels during the whole life service period, for further precise analysis of the accumulated fatigue damage at the sealed part of the edge bond. By the estimation of the wind occurrence regularity based on wind pressure return period, the events of each wind speed interval during the whole life were obtained for the IGUs at 50m height in Beijing, which are in good agreement with the measured data. Also, the wind-induced deflection analysis method of IGUs based on the formula of airspace coefficient was proposed and verified as an improvement of the original stiffness distribution method with the average relative error compared to the test being about 3% or less. Combining the two methods above, the deformation of the outer and inner panes under wind loads during 30 years was precisely calculated, and the deflection and stress state at selected locations were obtained finally. The results show that the compression displacement at the secondary sealant under the maximum wind pressure is close to 0.3mm (strain 2.5%), and the IGUs are in tens of thousands of times the low amplitude tensile-compression cycle and several times to dozens of times the relatively high amplitude tensile-compression cycle environment. The approach proposed in this paper provides a basis for subsequent studies on the durability of IGUs and the wind-resistant behaviors of curtain wall structures.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.77-87
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• 2023

Wind turbines playing a critical role in renewable energy generation, accurately assessing their operational status is crucial for maximizing energy production and minimizing downtime. This study conducts a comparative analysis of different neural network models for wind turbine condition diagnosis, evaluating their effectiveness using a dataset containing sensor measurements and historical turbine data. The study utilized supervisory control and data acquisition data, collected from 2 MW doubly-fed induction generator-based wind turbine system (Model HQ2000), for the analysis. Various neural network models such as artificial neural network, long short-term memory, and recurrent neural network were built, considering factors like activation function and hidden layers. Symmetric mean absolute percentage error were used to evaluate the performance of the models. Based on the evaluation, conclusions were drawn regarding the relative effectiveness of the neural network models for wind turbine condition diagnosis. The research results guide model selection for wind turbine condition diagnosis, contributing to improved reliability and efficiency through advanced neural network-based techniques and identifying future research directions for further advancements.

• Atmosphere
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• v.33 no.5
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• pp.549-560
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• 2023

This study evaluates three distinct observation methods, CRDS, OA-ICOS, and OF-CEAS, in greenhouse gas monitoring equipment for atmospheric CO₂ and CH₄ concentrations. The assessment encompasses fundamental performance, high-concentration measurement accuracy, calibration methods, and the impact of atmospheric humidity on measurement accuracy. Results indicate that within a range of approximately 500 ppm, all three devices demonstrate high accuracy and linearity. However, beyond 1000 ppm, CO₂ accuracy sharply declines (84%), emphasizing the need for caution when interpreting high-concentration CO₂ data. An analysis of calibration methods reveals that both CO₂ and CH₄ measurements achieve high accuracy and linearity through 1-point calibration, suggesting that multi-point calibration is not imperative for precision. In dynamic atmospheric conditions with significant CO₂ and CH₄ concentration variations, a 1-point calibration suffices for reliable data (99% accuracy). The evaluation of humidity impact demonstrates that humidity removal devices significantly reduce air moisture levels, yet this has a negligible effect on dry CO₂ concentrations (less than 0.5% relative error). All three observation method instruments, which have integrated humidity correction to calculate dry CO₂ concentrations, exhibit minor sensitivity to humidity removal devices, implying that additional removal devices may not be essential. Consequently, this study offers valuable insights for comparing data from different measurement devices and provides crucial information to consider in the operation of monitoring sites.

• Composites Research
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• v.36 no.6
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• pp.416-421
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• 2023

Multifunctional composite materials capable of both load-carrying and energy functions are promising innovative candidates for the advancement of contemporary technologies owing to their relative feasibility, cost-effectiveness, and optimized performance. Carbon fiber (CF)-based structural batteries utilize the graphitic inherent structure to enable the employment of carbon fibers as electrodes, current collectors, and reinforcement, while the matrix system is an ion-conduction and load transfer medium. Although it is possible to enhance performance through the modification of constituents, there remains a need for a systematic design methodology scheme to streamline the commercialization of structural batteries. In this work, a bi-phasic epoxy-based ionic liquid (IL) modified structural battery electrolyte (SBE) was developed via thermally initiated phase separation. The polymer's morphological, mechanical, and electrochemical characteristics were studied. In addition, the interfacial shear strength (IFSS) between CF/SBE was investigated via microdroplet tests. The results accentuated the significance of considering IFSS and matrix plasticity in designing composite structural batteries. This approach is expected to lay the foundation for realizing smart structures with optimized performance while minimizing the need for extensive trial and error, by paving the way for a streamlined computational design scheme in the future.