• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.235-242
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• 2022

Compared with buildings that have already been constructed, buildings under construction may be more vulnerable to such natural disasters as earthquakes because the concrete strength is not yet sufficient. Currently, Korean design standards present minimum performance targets for each seismic grade of buildings, but the seismic load for design is based on a return period of 2400 years. However, because the construction period of the building is much shorter than the period of use of the building, the application of the earthquake return period of 2400 years to buildings under construction may be excessive. Therefore, in this study, a construction stage model of buildings with 5, 15, 25, and 60 floors was created to analyze earthquake loads during construction of residential reinforced concrete (RC) buildings. The structural stability was confirmed by applying reduced seismic loads according to the return period. As a result, the structural stability was checked for an earthquake of the return period selected according to the construction period, and the earthquake return period that can secure structural safety according to the size of the building was confirmed.

• Proceedings of the SCSK Conference
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• 2003.09a
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• pp.578-589
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• 2003

The fuzzy rat that expresses hypersecretion of sebum and hyperplastic sebaceous glands is a genetic mutant for the study of many pharmacological aspects especially human acne. Through this model, we examined the effects of several phospholipids on the secretion of sebum after topical application. The phospholipid derivatives were phosphatidylcholine (PC), hydrogenated phosphatidylcholine (HPC), phosphati dylserine (PS) and hydrogenated phosphatidylserine(HPS). All agents were dissolved into the vehicle (1, 3-Butanediol, ethanol and water) at 0.5％ weight volume and applied on the dorsal area of the fuzzy rat. To observe histological changes, the skin biopsies were stained with Oil Red O and the size and morphology of sebaceous gland was observed under microscope. Topical treatment with PC and/or HPC showed a marked decrease in sebum excretion. Especially hydrogenated PC (HPC) appeared to have more predominant sebosuppressive function than any other treatment. The other agents such as PS and HPS showed a marginal effect on sebum secretion. With the sebosuppressive activity, HPC and PC seem to have a good potential application on acne treatment. In order to obtain more insights into possible mechanisms behind the above observations, effects of each phospholipid on the expression of peroxisome proliferator-activated receptor (PPAR) genes were investigated. Recently, it has been demonstrated that expression and activation of PPAR subtypes appear to modulate the accumulation of cytoplasmic fat droplets that characterizes the sebocyte differentiation(1). It was also previously suggested that PPAR${\gamma}$ antagonist would seem possible to interfere sebum production without side effects (2). In this study we examined the diverse effects of the tested phospholipids on the expression of several PPAR genes based on reverse transcription-polymerase chain reaction (RT-PCR) from the topically treated skin of fuzzy rats. The results and possible implications are discussed.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.97-108
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• 2023

Two carbonaceous adsorbents CAT and CARBOPAL were tested for reducing the concentration of the three herbicides in water: 2,4-D (2,4-dichlorophenoxyacetic acid), TCP (2,4,6-trichlorophenol) and metolachlor. Textural and chemical characterization of the adsorbents include nitrogen isotherms, FTIR, titration and thermogravimetric analyses. Adsorption was studied in discontinuous adsorption experiments at different pH values. The experimental adsorption isotherms data were fitted to four theoretical models. Adsorbent characterization reveals that CAT has higher micropore area, lower pore diameter and lower acidity than CARBOPAL. The adsorption is a second-order process and the isotherms best fitted to Sips model. The efficiency of the process depends mainly on the charge of the adsorbate for TCP and 2,4-D, but it depends on the charge of the surface for metolachlor. Adsorption capacity is higher on CAT for 2,4-D and TCP (small molecules), and it is higher on CARBOPAL for metolachlor (large molecules). Theoretical calculations clearly support this assumption.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.895-904
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• 2008

CWR (Continuous Welded Rail) may be broken when a temperature drop below the neutral temperature changes in axial force, causing tensile fracture and rail gap, in winter. Rail-breaks may lead to the damage of the rail and wheel by dynamic load, and the reduction of running safety if not detected before the passage of a train. In this study, the track and train coupled model with open gap for dynamic interaction analysis, is proposed. Linear track and train systems is coupled by the nonlinear Herzian contact spring and the complete system matrices of total track-train system is constructed. And the interaction phenomenon considering open gap, was defined by assigning the irregularity functions between the two sides of a gap. Time history analysis, which have an iteration scheme such as $Newmark-{\beta}$ method based on Modified Newton-Raphson methods, was performed to solve the nonlinear equation. Finally, numerical studies are performed to assess the effect of various parameters of system, apply to various speeds, open gap size and the support stiffness of rail.

• Journal of Coastal Disaster Prevention
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• v.6 no.3
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• pp.111-120
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• 2019

In coastal morphological modelling, there are a number of input factors: wave height, water depth, sand particle size, bed friction coefficients, coastal structures and so forth. Measurements or estimates of these input data may include uncertainties due to errors by the measurement or hind-casting methods. Therefore, it is necessary to consider the uncertainty of each input data and the range of the uncertainty during the evaluation of numerical results. In this study, three uncertainty factors are considered with regard to the prediction of coastal erosion in Ilsan beach located in Ilsan-dong, Ulsan metropolitan city. Those are wave diffraction effect of XBeach model, wave input scenario and the specification of the coastal structure. For this purpose, the values of mean wave direction, significant wave height and the height of the submerged breakwater were adjusted respectively and the followed numerical results of morphological changes are analyzed. There were erosion dominant patterns as the wave direction is perpendicular to Ilsan beach, the higher significant wave height, and the lower height of the submerged breakwater. Furthermore, the rate of uncertainty impacts among mean wave direction, significant wave height and the height of the submerged breakwater are compared. In the study area, the uncertainty influence by the wave input scenario was the largest, followed by the height of the submerged breakwater and the mean wave direction.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.75-75
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• 2022

Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.

• Journal of Microbiology and Biotechnology
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• v.33 no.8
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• pp.1013-1022
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• 2023

Arbuscular mycorrhizal fungi (AMF) are widespread soil endophytic fungi, forming mutualistic relationships with the vast majority of land plants. Biochar (BC) has been reported to improve soil fertility and promote plant growth. However, limited studies are available concerning the combined effects of AMF and BC on soil community structure and plant growth. In this work, a pot experiment was designed to investigate the effects of AMF and BC on the rhizosphere microbial community of Allium fistulosum L. Using Illumina high-throughput sequencing, we showed that inoculation of AMF and BC had a significant impact on soil microbial community composition, diversity, and versatility. Increases were observed in both plant growth (the plant height by 8.6%, shoot fresh weight by 12.1%) and root morphological traits (average diameter by 20.5%). The phylogenetic tree also showed differences in the fungal community composition in A. fistulosum. In addition, Linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed that 16 biomarkers were detected in the control (CK) and AMF treatment, while only 3 were detected in the AMF + BC treatment. Molecular ecological network analysis showed that the AMF + BC treatment group had a more complex network of fungal communities, as evidenced by higher average connectivity. The functional composition spectrum showed significant differences in the functional distribution of soil microbial communities among different fungal genera. The structural equation model (SEM) confirmed that AMF could improve the microbial multifunctionality by regulating the rhizosphere fungal diversity and soil properties. Our findings provide new information on the effects of AMF and biochar on plants and soil microbial communities.

• Korea Trade Review
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• v.45 no.2
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• pp.229-262
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• 2020

The price-to-earnings ratio (PER) is an important indicator to measure the stock price and profitability of a firm; it is also the most used valuation indicator among investors. When using the PER to compare the investment values of different stocks, these stocks must come from the same sector. This study mainly focuses on the China's listed manufacturing firms. By learning from previous research results and analyzing the current situation, we studied the correlation between the manufacturing sector's PER and its influencing factors from both macro and micro perspectives, the combination of which eventually sheds light on such correlation. Analyzing GDP growth rate data, Manufacturing Purchasing Managers' Index, and other macroeconomic variables from 2008 to 2018, we conclude that these variables jointly have a certain impact on the average PER of the manufacturing sector. We then form panel data based on relevant (2014-2018) data gathered from 317 of China's A-listed manufacturing firms to study the impact of micro-variables on PER. By using Stata and other software to analyze the panel data, we reach the conclusion that the Debt to Asset Ratio, Return on Equity, EPS growth rate, Operating Profit Ratio, Dividend Payout Ratio, and firm size have a significant impact on PER. The Current Ratio, Treasury Stock ratio and Ownership Concentration have no distinct effect on PER. Based on our empirical findings, we design a theoretical model that affects the PER.

• Biomolecules & Therapeutics
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• v.32 no.2
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• pp.214-223
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• 2024

Metabolic abnormalities in the liver are closely associated with diverse metabolic diseases such as non-alcoholic fatty liver disease, type 2 diabetes, and obesity. The aim of this study was to evaluate the ameliorating effect of robinetin (RBN) on the significant pathogenic features of metabolic failure in the liver and to identify the underlying molecular mechanism. RBN significantly decreased triglyceride (TG) accumulation by downregulating lipogenesis-related transcription factors in AML-12 murine hepatocyte cell line. In addition, mice fed with Western diet (WD) containing 0.025% or 0.05% RBN showed reduced liver mass and lipid droplet size, as well as improved plasma insulin levels and homeostatic model assessment of insulin resistance (HOMA-IR) values. CD38 was identified as a target of RBN using the BioAssay database, and its expression was increased in OPA-treated AML-12 cells and liver tissues of WD-fed mice. Furthermore, RBN elicited these effects through its anti-histone acetyltransferase (HAT) activity. Computational simulation revealed that RBN can dock into the HAT domain pocket of p300, a histone acetyltransferase, which leads to the abrogation of its catalytic activity. Additionally, knock-down of p300 using siRNA reduced CD38 expression. The chromatin immunoprecipitation (ChIP) assay showed that p300 occupancy on the promoter region of CD38 was significantly decreased, and H3K9 acetylation levels were diminished in lipid-accumulated AML-12 cells treated with RBN. RBN improves the pathogenic features of metabolic failure by suppressing the p300-CD38 axis through its anti-HAT activity, which suggests that RBN can be used as a new phytoceutical candidate for preventing or improving this condition.