• Smart Structures and Systems
• /
• v.31 no.2
• /
• pp.101-111
• /
• 2023

Structural health monitoring (SHM) covers a range of damage detection strategies for buildings. In real-time, SHM provides a basis for rapid decision making to optimise the speed and economic efficiency of post-event response. Previous work introduced an SHM method based on identifying structural nonlinear hysteretic parameters and their evolution from structural force-deformation hysteresis loops in real-time. This research extends and generalises this method to investigate the impact of a wide range of flag-shaped or pinching shape nonlinear hysteretic response and its impact on the SHM accuracy. A particular focus is plastic stiffness (K_p), where accurate identification of this parameter enables accurate identification of net and total plastic deformation and plastic energy dissipated, all of which are directly related to damage and infrequently assessed in SHM. A sensitivity study using a realistic seismic case study with known ground truth values investigates the impact of hysteresis loop shape, as well as added noise, on SHM accuracy using a suite of 20 ground motions from the PEER database. Monte Carlo analysis over 22,000 simulations with different hysteresis loops and added noise resulted in absolute percentage identification error (median, (IQR)) in K_p of 1.88% (0.79, 4.94)%. Errors were larger where five events (Earthquakes #1, 6, 9, 14) have very large errors over 100% for resulted K_p as an almost entirely linear response yielded only negligible plastic response, increasing identification error. The sensitivity analysis shows accuracy is reduces to within 3% when plastic drift is induced. This method shows clear potential to provide accurate, real-time metrics of non-linear stiffness and deformation to assist rapid damage assessment and decision making, utilising algorithms significantly simpler than previous non-linear structural model-based parameter identification SHM methods.

• Journal of Korea Foresty Energy
• /
• v.18 no.2
• /
• pp.84-91
• /
• 1999

The objective of this study was to present creep and the effects of mechano-sorptive deflection of drift pin moment resisting joint between LVL members under changing relative humidity (RH) conditions. The LVL members with steel gusset were jointed by a square pattern of eight injected drift pin. Three diameter drift pins were used to test specimens (6mm, 10mm, and 16mm). The creep test was conducted under two constant loading conditions : one at 30 kgf(840 kgf-cm) and the other at 60 kgf(1680 kgf-cm). The experiment was conducted in an open shed outside. (1)The total rotation creep model of moment resisting joing can be expressed as the sum of the creep of controlled environment (3-parameter model), dimensional change and mechano-sorptive deflection resulting from the variable environment. (2)Mechanosorptive rotation creep is recoverable as moisture content increases during adsorption. Least squares method for linear regression analysis was performed using mechano-sorptive rotation creep as the dependent variable and moisture content as the independent variable. The slope of low moment specimens are compared with those of high moment. This means that low moment condition is more easily affected by changes in humidity than high moment conditions. (3)Although creep deflection is higher for small diameter drift pin than for large diameter drift pin, the shape of creep deflection curves for all specimens is similar.

• Nutrition Research and Practice
• /
• v.9 no.6
• /
• pp.644-649
• /
• 2015

BACKGROUND/OBJECTIVES: Targeting consumers who consume lunches at their worksite cafeterias would be a valuable approach to reduce sodium intake in South Korea. To assess the relationships between socio-demographic factors, consumer satisfaction, attitudes, barriers and the frequency of sodium-reduced meal intake. SUBJECTS/METHODS: We implemented a cross-sectional research, analyzing data from 738 consumers aged 18 years or older (327 males and 411 females) at 17 worksite cafeterias in South Korea. We used the ordinary least squares regression analysis to determine the factors related to overall satisfaction with sodium-reduced meal. General linear models with LSD tests were employed to examine the variables that differed by the frequency of sodium-reduced meal intake. RESULTS: Most subjects always or usually consumed the sodium-reduced meal (49%), followed by sometimes (34%) and rarely or never (18%). Diverse menus, taste and belief in the helpfulness of the sodium-reduced meal significantly increased overall satisfaction with the sodium-reduced diet (P < 0.05). We found importance of needs in the following order: 1) 'menu diversity' (4.01 points), 2) 'active promotion' (3.97 points), 3) 'display of nutrition labels in a visible location' (3.96 points), 4) 'improvement of taste' (3.88 points), and 5) 'education of sodium-reduction self-care behaviors' (3.82 points). CONCLUSION: Dietitians could lead consumers to choose sodium-reduced meals by improving their taste and providing diverse menus for the sodium-reduced meals at worksite cafeterias.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.6
• /
• pp.1075-1083
• /
• 2009

The scientific research method went through construction of hypothesis and collection of data by experiment or observation and abstracting the hypothesis based on the experience which uses the data. The statistical methodology plays an important role in this process. The method which acquires a data becomes an initial process of abstraction and a survey research using structured questionnaires is a basic tool. After the data is acquired, the high-class statistical techniques such as the regression analysis and the linear structural equation model are used to abstract a hypothesis. By the way, from time to time the concepts which have become abstractive do not help us to understand an actual phenomena, rather it is need to extract some knowledge from questions themselves. In this article, we review the well known statistical methods providing the ways of finding core questions which possibly answer a researcher wants to know. We deal with course evaluation data as an example and try to set up the strategy for improving course evaluation.

• The Korean Journal of Applied Statistics
• /
• v.18 no.2
• /
• pp.253-269
• /
• 2005

One of the basic assumptions of the regression models is that the parameter vector does not vary across sample observations. If the parameter vector is not constant for all observations in the sample, the statistical model is changed and the usual least squares estimators do not yield unbiased, consistent and efficient estimates. This study investigates the regression model with some or all parameters vary across partitions of the whole sample data when the model permits different response coefficients during unusual time periods. Since the usual test for overall homogeneity of regressions across partitions of the sample data does not explicitly identify the break points between the partitions, the testing the equality between subsets of coefficients in two or more linear regressions is generalized and combined with the test procedure to search the break point. The method is applied to find the possibility and the turning point of the structural change in the long-run unemployment rate in the usual static framework by using the regression model. The relationships between the variables included in the model are reexamined in the dynamic framework by using Vector Autoregression.

• Journal of Biosystems Engineering
• /
• v.43 no.2
• /
• pp.138-147
• /
• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• Journal of Korean Society for Atmospheric Environment
• /
• v.26 no.5
• /
• pp.533-542
• /
• 2010

The $PM_{10}$ concentrations in the underground should be monitored for the health of commuters on the underground subway system. Seoul Metro and Seoul Metropolitan Rapid Transit Corporation are measuring several air pollutants regularly. As for the measurement of $PM_{10}$ concentrations, instruments based on $\beta$-ray absorption method and gravimetric methods are being used. But the instruments using gravimetric method give us 20-hour-average data and the $\beta$-ray instruments can measure the $PM_{10}$ concentration every one hour. In order to keep the $PM_{10}$ concentrations under a healthy condition, the air quality of the underground platform and tunnels should be monitored and controlled continuously. The $PM_{10}$ instruments using light scattering method can measure the $PM_{10}$ concentrations every less than one minute. However, the reliability of the instruments using light scattering method is still not proved. The purpose of this work is to study the reliability of the instruments using light scattering method to measure the $PM_{10}$ concentrations continuously in the underground platforms. One instrument using $\beta$-ray absorption method and two different instruments using light scattering method (LSM1, LSM2) were placed at the platform of the Jegi station of Seoul metro line Number 1 for 10 days. The correlation between the $\beta$-ray instrument and the LSM2 ($r^2$=0.732) was higher than that between the $\beta$-ray instrument and the LSM1 ($r^2$=0.393). Thus the LSM2 was chosen for further analysis. Three different regression analysis methods were tested: Linear regression analysis, Nonlinear regression analysis and Orthogonal regression analysis. When the instruments using light scattering method were used, the data measured these instruments have to be converted to actual $PM_{10}$ concentrations using some factors. With these analyses, the factors could be calculated successfully as linear and nonlinear forms with respect to the data. And the orthogonal regression analysis was performed better than the ordinary least squares method by 28.45% reduction of RMSE. These findings propose that the instruments using light scattering method light scattering method can be used to measure and control the $PM_{10}$ concentrations of the underground subway stations.

• Computers and Concrete
• /
• v.8 no.3
• /
• pp.293-309
• /
• 2011

A long-term structural health monitoring (SHM) system comprising over 700 sensors of sixteen types has been implemented on the Guangzhou Television and Sightseeing Tower (GTST) of 610 m high for real-time monitoring of the structure at both construction and service stages. As part of this sophisticated SHM system, 48 temperature sensors have been deployed at 12 cross-sections of the reinforced concrete inner structure of the GTST to provide on-line monitoring via a wireless data transmission system. In this paper, the differential temperature profiles in the reinforced concrete inner structure of the GTST, which are mainly caused by solar radiation, are recognized from the monitoring data with the purpose of understanding the temperature-induced structural internal forces and deformations. After a careful examination of the pre-classified temperature measurement data obtained under sunny days and non-sunny days, common characteristic of the daily temperature variation is observed from the data acquired in sunny days. Making use of 60-day temperature measurement data obtained in sunny days, statistical patterns of the daily rising temperature and daily descending temperature are synthesized, and temperature distribution models of the reinforced concrete inner structure of the GTST are formulated using linear regression analysis. The developed monitoring-based temperature distribution models will serve as a reliable input for numerical prediction of the temperature-induced deformations and provide a robust basis to facilitate the design and construction of similar structures in consideration of thermal effects.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.54 no.1
• /
• pp.29-35
• /
• 2009

The aim of the present study was to update the calibration that is used for the measurement of the total nitrogen content in the rice plant samples by using the visible and near infrared spectrum. Before the equation merge, correlation coefficient of calibration equation for nitrogen content on each rice parts was 0.945 (Leaf), 0.928 (Stem), and 0.864 (Whole plant), respectively. In the calibration models created by each part in the rice plant under the various regression method, the calibration model for the leaf was recorded with relatively high accuracy. Among of those, the calibration equation developed by Partial least squares (PLS) method was more accurate than the Multiple linear regression (MLR) method. The calibration equation was sensitive based on variety and location variations. However, we have merged and enlarged various of the samples that made not only to measure the nitrogen content more accurately, but also later sampling populations became more diversified. After merging, $R^2$ value becomes more accurate and significantly to 0.950 (L.), 0.974 (S.), 0.940 (W.). Also, after removal of outlier, R2 values increased into 0.998, 0.995, and 0.997. In view of the results so far achieved, Standard error of prediction (SEP) and SEP (C) were reduced in the stem and whole plant. Biases were reduced in the leaf, stem as well as whole plant. Slopes were high in the stem. Standard deviation reduced in the stem but $R^2$ was high in the stem and whole plant. Result was indicated that calibration equation make update, and updating robust calibration equation from merge function and multi-variate calibration.

• The Korean Journal of Pain
• /
• v.25 no.1
• /
• pp.1-6
• /
• 2012

Background: Curcumin has been reported to have anti-inflammatory, antioxidant, antiviral, antifungal, antitumor, and antinociceptive activity when administered systemically. We investigated the analgesic efficacy of intrathecal curcumin in a rat model of inflammatory pain. Methods: Male Sprague Dawley rats were prepared for intrathecal catheterization. Pain was evoked by injection of formalin solution (5%, $50{\mu}l$) into the hind paw. Curcumin doses of 62.5, 125, 250, and $500{\mu}g$were delivered through an intrathecal catheter to examine the flinching responses. The $ED_{50}$ values (half-maximal effective dose) with 95% confidence intervals of curcumin for both phases of the formalin test were calculated from the dose-response lines fitted by least-squares linear regression on a log scale. Results: In rats with intrathecal administration of curcumin, the flinching responses were significantly decreased in both phases. The slope of the regression line was significantly different from zero only in phase 2, and the $ED_{50}$ value (95% confidence interval) of curcumin was $511.4{\mu}g$ (23.5-1126.5). There was no apparent abnormal behavior following the administration of curcumin. Conclusions: Intrathecal administration of curcumin decreased inflammatory pain in rats, and further investigation to elucidate the precise mechanism of spinal action of curcumin is warranted.