• Safety and Health at Work
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• v.10 no.2
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• pp.196-204
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• 2019

Background: Liquid chromatography-tandem mass spectrometry (LC-MSMS) for simultaneous analysis of multiple microbial secondary metabolites (MSMs) is potentially subject to interference by matrix components. Methods: We examined potential matrix effects (MEs) in analyses of 31 MSMs using ultraperformance LC-MSMS. Twenty-one dust aliquots from three buildings (seven aliquots/building) were spiked with seven concentrations of each of the MSMs ($6.2pg/{\mu}l-900pg/{\mu}l$) and then extracted. Another set of 21 aliquots were first extracted and then, the extract was spiked with the same concentrations. We added deepoxy-deoxynivalenol (DOM) to all aliquots as a universal internal standard. Ten microliters of the extract was injected into the ultraperformance LC-MSMS. ME was calculated by subtracting the percentage of the response of analyte in spiked extract to that in neat standard from 100. Spiked extract results were used to create a matrix-matched calibration (MMC) curve for estimating MSM concentration in dust spiked before extraction. Results: Analysis of variance was used to examine effects of compound (MSM), building and concentration on response. MEs (range: 63.4%-99.97%) significantly differed by MSM (p < 0.01) and building (p < 0.05). Mean percent recoveries adjusted with DOM and the MMC method were 246.3% (SD = 226.0) and 86.3% (SD = 70.7), respectively. Conclusion: We found that dust MEs resulted in substantial underestimation in quantifying MSMs and that DOM was not an optimal universal internal standard for the adjustment but that the MMC method resulted in more accurate and precise recovery compared with DOM. More research on adjustment methods for dust MEs in the simultaneous analyses of multiple MSMs using LC-MSMS is warranted.

• Journal of Ginseng Research
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• v.43 no.4
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• pp.508-516
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• 2019

Background: Ginsenosides are not only the principal bioactive components but also the important indexes to the quality assessment of Panax ginseng Meyer. Their contents in cultivated ginseng vary with the growth environment and age. The present study aimed at evaluating the significant difference between 36 cultivated ginseng of different cultivation areas and ages based on the simultaneously determined contents of 14 ginsenosides. Methods: A high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometer (MS) method was developed and used in the multiple reaction-monitoring (MRM) mode (HPLC-MRM/MS) for the quantitative analysis of ginsenosides. Multivariate statistical analysis, such as principal component analysis and partial least squares-discriminant analysis, was applied to discriminate ginseng samples of various cultivation areas and ages and to discover the differentially accumulated ginsenoside markers. Results: The developed HPLC-MRM/MS method was validated to be precise, accurate, stable, sensitive, and repeatable for the simultaneous determination of 14 ginsenosides. It was found that the 3- and 5-yr-old ginseng samples were differentiated distinctly by all means of multivariate statistical analysis, whereas the 4-yr-old samples exhibited similarity to either 3- or 5-yr-old samples in the contents of ginsenosides. Among the 14 detected ginsenosides, Rg1, Rb1, Rb2, Rc, 20(S)-Rf, 20(S)-Rh1, and Rb3 were identified as potential markers for the differentiation of cultivation ages. In addition, the 5-yr-old samples were able to be classified in cultivation area based on the contents of ginsenosides, whereas the 3- and 4-yr-old samples showed little differences in cultivation area. Conclusion: This study demonstrated that the HPLC-MRM/MS method combined with multivariate statistical analysis provides deep insight into the accumulation characteristics of ginsenosides and could be used to differentiate ginseng that are cultivated in different areas and ages.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.485-493
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• 2004

The system performance of 2-Dimensional wavelength hopping/time spreading optical CDMA systems is found to be limited by the occurrence of the beat noise between the components of the signal and the multiple user interference. This paper shows that the performance is analyzed under the beat noise and no beat noise to blow impact of the beat noise. To overcome this problem, the OHL(Optical Hard-Limiter) is used in the receiver. The performance is calculated for a optical CDMA system employing asymmetric and symmetric prime-hop 2-Dimensional codes, respectively The analysis results show that the performance improved 3.5 times of simultaneous users of before and after inserting OHL in the case of no beat noise. In the case of beat noise the performance improved 1.5 times of simultaneous users of before and after inserting OHL. The performance marked use of symmetric prime-hop code.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2647-2655
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• 2002

This research presents an analytical model to investigate the stability due to the ball bearing waviness i n a rotating system supported by two ball bearings. The stiffness of a ball bearing changes periodically due to the waviness in the rolling elements as the rotor rotates, and it can be calculated by differentiating the nonlinear contact forces. The linearized equations of motion can be represented as a parametrically excited system in the form of Mathieu's equation, because the stiffness coefficients have time -varying components due to the waviness. Their solution can be assumed as a Fourier series expansion so that the equations of motion can be rewritten as the simultaneous algebraic equations with respect to the Fourier coefficients. Then, stability can be determined by solving the Hill's infinite determinant of these algebraic equations. The validity of this research is proved by comparing the stability chart with the time responses of the vibration model suggested by prior researches. This research shows that the waviness in the rolling elements of a ball bearing generates the time-varying component of the stiffness coefficient, whose frequency is called the frequency of the parametric excitation. It also shows that the instability takes place from the positions in which the ratio of the natural frequency to the frequency of the parametric excitation corresponds to i/2 (i=1,2,3..).

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.967-973
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• 2021

In 2011, an earthquake and subsequent tsunami hit the Fukushima Daiichi Nuclear Power Plant, causing simultaneous accidents in several reactors. This accident shows us that if there are several reactors on site, the seismic risk to multiple units is important to consider, in addition to that to single units in isolation. When a seismic event occurs, a seismic-failure correlation exists between the nuclear power plant's structures, systems, and components (SSCs) due to their seismic-response and seismic-capacity correlations. Therefore, it is necessary to evaluate the multi-unit seismic risk by considering the SSCs' seismic-failure-correlation effect. In this study, a methodology is proposed to obtain the seismic-response-correlation coefficient between SSCs to calculate the risk to multi-unit facilities. This coefficient is calculated from a probabilistic multi-unit seismic-response analysis. The seismic-response and seismic-failure-correlation coefficients of the emergency diesel generators installed within the units are successfully derived via the proposed method. In addition, the distribution of the seismic-response-correlation coefficient was observed as a function of the distance between SSCs of various dynamic characteristics. It is demonstrated that the proposed methodology can reasonably derive the seismic-response-correlation coefficient between SSCs, which is the input data for multi-unit seismic probabilistic safety assessment.

• Korean Journal of Pharmacognosy
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• v.50 no.1
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• pp.65-71
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• 2019

One of the oriental medicine prescriptions, Sagunja-tang consists of four herbal medicines (Ginseng Radix, Poria Sclerotium, Atractylodis Rhizoma Alba, and Glycyrrhiziae Radix et Rhizoma) and has been used as a medicine to enhance tonify the function of spleen and stomach in Korea. In this study, we conducted simultaneous analysis of the 9 marker components, liquiritin apioside, liquiritin, ginsenoside Rg1, liquiritigenin, ginsenoside Rb1, glycyrrhizin, atractylenolide III, atractylenolide II, and atractylenolide I in Sagunja-tang using a liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS). Marker compounds were separated on a Waters Acquity UPLC BEH $C_{18}$ analytical column ($2.1{\times}100mm$, 1.7 mm) and the column was maintained at $45^{\circ}C$. The mobile phase consists of 0.1% (v/v) aqueous formic acid and acetonitrile with gradient condition. The LC-MS analysis was performed using a Waters ACQUITY TQD LC-MS/MS system with multiple reaction monitoring (MRM) method in the positive and negative modes. The calibration curves of the nine marker components showed good linearity with coefficient of determination ${\geq}0.9984$ within tested range. The limits of detection and limits of quantification values were 0.27-2.42 ng/mL and 0.81-7.27 ng/mL, respectively. The concentrations of tested 9 analytes in the lyophilized Sagunja-tang sample using the established LC-ESI-MS/MS MRM method were detected up to 16.593 mg/g. These results can be useful as a basic data for the quality control of an oriental medicine prescriptions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.149-158
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• 2019

The scheduling of planned maintenance problem of a system consisting of a number of components was studied. The purpose of maintenance scheduling is to minimize the cost of maintaining long-term operations. On the system side, the cost of a system shutdown can be minimized by grouping and inspecting a number of components. In addition, proper inspection cycles can be selected for each component to identify the failure sufficiently early to minimize the cost of the failure. To reduce the complexity of the calculations, the 'base interval approach' used in previous studies was applied and, in addition, the inspection cost savings from simultaneous inspections of multiple components were considered. To compare the effectiveness of inspection cost savings, this paper presents the results of simulation analysis performed by referring to the cases in the existing studies.

• Wind and Structures
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• v.11 no.1
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• pp.35-50
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• 2008

Wind and temperature have been shown to be the critical sources causing changes in the modal properties of large-scale bridges. While the individual effects of wind and temperature on modal variability have been widely studied, the investigation about the effects of multiple environmental factors on structural modal properties was scarcely reported. This paper addresses the modeling of the simultaneous effects of wind and temperature on the modal frequencies of an instrumented cable-stayed bridge. Making use of the long-term monitoring data from anemometers, temperature sensors and accelerometers, a neural network model is formulated to correlate the modal frequency of each vibration mode with wind speed and temperature simultaneously. Research efforts have been made on enhancing the prediction capability of the neural network model through optimal selection of the number of hidden nodes and an analysis of relative strength of effect (RSE) for input reconstruction. The generalization performance of the formulated model is verified with a set of new testing data that have not been used in formulating the model. It is shown that using the significant components of wind speeds and temperatures rather than the whole measurement components as input to neural network can enhance the prediction capability. For the fundamental mode of the bridge investigated, wind and temperature together apply an overall negative action on the modal frequency, and the change in wind condition contributes less to the modal variability than the change in temperature.

• Bulletin of the Korean Chemical Society
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• v.28 no.7
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• pp.1187-1194
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• 2007

The three major active isoflavonoids (calycosin-7-O-β -glucoside, isomucronulatol 7-O-β-glucoside, formononetin) and two main saponins (astragaloside I, astragaloside IV) in an extract of Radix Astragali were determined using rapid, sensitive, reliable HPLC/UV and LC-ESI-MS/MS methods. The separation conditions employed for HPLC/UV were optimized using a phenyl-hexyl column (4.6 × 150 mm, 5 μm) with the gradient elution of acetonitrile and water as the mobile phase at a flow rate of 1.0 mL/min and a detection wavelength of 230 nm. The specificity of the peaks was determined using a triple quadrupole tandem mass spectrometer equipped with an electrospray ionization (ESI) source that was operated in multiple reaction monitoring (MRM) in the positive mode. These methods were fully validated with respect to the linearity, accuracy, precision, recovery and robustness. The HPLC/UV method was applied successfully to the quantification of three major isoflavonoids in the extract of Radix Astragali. The results indicate that the established HPLC/UV and LC-ESI-MS/MS methods are suitable for the quantitative analysis and quality control of multi-components in Radix Astragali.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.1957-1980
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• 2021

The significant aim of this research has always been to evaluate the mechanism for efficient and inherently aware usage of vitality in-home devices, thus improving the information of smart metering systems with regard to the usage of selected homes and the time of use. Advances in information processing are commonly used to quantify gigantic building activity data steps to boost the activity efficiency of the building energy systems. Here, some smart data mining models are offered to measure, and predict the time series for energy in order to expose different ephemeral principles for using energy. Such considerations illustrate the use of machines in relation to time, such as day hour, time of day, week, month and year relationships within a family unit, which are key components in gathering and separating the effect of consumers behaviors in the use of energy and their pattern of energy prediction. It is necessary to determine the multiple relations through the usage of different appliances from simultaneous information flows. In comparison, specific relations among interval-based instances where multiple appliances use continue for certain duration are difficult to determine. In order to resolve these difficulties, an unsupervised energy time-series data clustering and a frequent pattern mining study as well as a deep learning technique for estimating energy use were presented. A broad test using true data sets that are rich in smart meter data were conducted. The exact results of the appliance designs that were recognized by the proposed model were filled out by Deep Convolutional Neural Networks (CNN) and Recurrent Neural Networks (LSTM and GRU) at each stage, with consolidated accuracy of 94.79%, 97.99%, 99.61%, for 25%, 50%, and 75%, respectively.