• Environmental Analysis Health and Toxicology
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• v.22 no.2 s.57
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• pp.111-118
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• 2007

This study was performed to measure gaseous Organochlorine Pesticides (OCPs : heptachlor epoxide, ${\alpha}/{\gamma}-chlordane$, trans-nonachlor, endosulfan, ${\gamma}-HCH$ and p, p'-DDE) concentration using PUF high volume sampler from June, 2000 to June, 2002 in the semi-rural atmosphere. Using monitoring data for two years, we tried to investigate the annual cycles of gaseous OCPs. We considered three functions to describe the annual cycle: Gaussian, Lorentzian and sinusoidal functions. These functions accounted for $54{\sim}91%$ of the variability in concentration for each gaseous OCPs, and the sinusoidal function gave the best fits. It was seen that the gaseous OCPs concentration increased during the warmer weather while decreased during colder weather. The variation of the gaseous OCPs concentration was closely similar to the variations of ambient temperature. The annual cycle of endosulfan was strongly higher than in comparison with other gaseous OCPs, while for ${\gamma}-HCH$, the cycle was weakly high and did not show apparent seasonal variation. The position of the annual maximum exists generally late July to early August. The period that showed levels more than a half maximum was from late June to early September.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Journal of Preventive Medicine and Public Health
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• v.34 no.2
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• pp.119-126
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• 2001

Air pollution epidemiologic studies are intrinsically difficult because the expected effect size at general environmental levels is small, exposure and misclassification of exposure are common, and exposure is not selective to a specific pollutant. In this review paper, epidemiologic study designs and analytic methods are described, and two nationwide projects on air pollution epidemiology are introduced. This paper also demonstrates that possible confounding issues in time-series analysis can be resolved and the impact on the use of data from ambient monitoring stations may not be critical. In this paper we provide a basic understanding of the types of air pollution epidemiologic study designs that be subdivided by the mode of air pollution effects on human health (acute or chronic). With the improvements in the area of air pollution epidemiologic studies, we should emphasize that elaborate models and statistical techniques cannot compensate for inadequate study design or poor data collection.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.2
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• pp.159-173
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• 1999

Based on air quality monitoring data('89~'97) operated by the Department of Environment, we provide various fundamental statistics for ground ozone. The purpose of this paper are to review the national ambient ozone standard, to study spatial distribution of ozone. Since we, in Korea, calculate average ozone level, to examine the occurrences of ozone level 3 times a day (1~8, 9~16, 17~24 hours), the method does not seem to be scientifically sound comparing to a running average method adapted by the USEPA. When we counted the number of cases with 8-h average O3 level exceeding 60ppb(8-h average standard in Korea)and 80 ppb (that in the U.S.A) and also when we calculated 8-hour average ozone level based on th US method, some regions were classified as non-attainment areas. Especially in Seoul, results of spatial distribution analysis showed that high level ozone over 80 ppb was observed at Kuui-Dong and Pangi-Dong in the eastern part and at Ssangmun-Dong in the northeastern part. Also, occurrences of ozone episode defined as number of days then ozone level exceeding 80 ppb for 3 consecutive hours were extensively reviewed in this paper.

• Smart Structures and Systems
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• v.2 no.3
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• pp.225-235
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• 2006

With the discovery in plants of the proteinaceous forisome crystalloid (Knoblauch, et al. 2003), a novel, non-living, ATP-independent biological material became available to the designer of smart materials for advanced actuating and sensing. The in vitro studies of Knoblauch, et al. show that forisomes (2-4 micron wide and 10-40 micron long) can be repeatedly stimulated to contract and expand anisotropically by shifting either the ambient pH or the ambient calcium ion concentration. Because of their unique abilities to develop and reverse strains greater than 20% in time periods less than one second, forisomes have the potential to outperform current smart materials as advanced, biomimetic, multi-functional, smart sensors or actuators. Probing forisome material properties is an immediate need to lay the foundation for synthesizing forisomebased smart materials for health monitoring of structural integrity in civil infrastructure and for aerospace hardware. Microfluidics is a growing, vibrant technology with increasingly diverse applications. Here, we use microfluidics to study the surface interaction between forisome and substrate and the conformational dynamics of forisomes within a confined geometry to lay the foundation for forisome-based smart materials synthesis in controlled and repeatable environment.

• Structural Engineering and Mechanics
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• v.15 no.1
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• pp.115-134
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• 2003

The Ting Kau Bridge in Hong Kong is a cable-stayed bridge comprising two main spans and two side spans. The bridge deck is supported by three towers, an end pier and an abutment. Each of the three towers consists of a single reinforced concrete mast which reduces its section in steps, and it is strengthened by transverse cables and struts in the transverse vertical plane. The bridge deck is supported by four inclined planes of cables emanating from anchorages at the tower tops. In view of the threat from typhoons, the dynamic behaviour of long-span cable-supported bridges in the region is always an important consideration in their design. This paper is devoted to the ambient vibration measurements of the bridge for evaluation of dynamic characteristics including the natural frequencies and mode shapes. It also describes the modelling of the bridge. A few finite element models are developed and calibrated to match with the field data and the results of subsequent structural health monitoring of the bridge.

• Structural Engineering and Mechanics
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• v.56 no.6
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• pp.939-957
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• 2015

In this paper, a new approach based on the continuum model is proposed to estimate the main cable tension force of suspension bridges from measured natural frequencies. This approach considered the vertical vibration of a main cable hinged at both towers and supported by an elastic girder and hangers along its entire length. The equation reflected the relationship between vibration frequency and horizontal tension force of a main cable was derived. To avoid to generate the additional cable tension force by sag-extensibility, the analytical solution of characteristic equation for anti-symmetrical vibration mode of the main cable was calculated. Then, the estimation of main cable tension force was carried out by anti-symmetric characteristic frequency vector. The errors of estimation due to characteristic frequency deviations were investigated through numerical analysis of the main cable of Taizhou Bridge. A field experiment was conducted to verify the proposed approach. Through measuring and analyzing the responses of a main cable of Taizhou Bridge under ambient excitation, the horizontal tension force of the main cable was identified from the first three odd frequencies. It is shown that the estimated results agree well with the designed values. The proposed approach can be used to conduct the long-term health monitoring of suspension bridges.

• Smart Structures and Systems
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• v.23 no.5
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• pp.507-520
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• 2019

In the structural health monitoring field, damage detection has been commonly carried out based on the structural model and the engineering features related to the model. However, the extracted features are often subjected to various errors, which makes the pattern recognition for damage detection still challenging. In this study, an automated damage identification method is presented for hanger cables in a tied-arch bridge using a convolutional neural network (CNN). Raw measurement data for Fourier amplitude spectra (FAS) of acceleration responses are used without a complex data pre-processing for modal identification. A CNN is a kind of deep neural network that typically consists of convolution, pooling, and fully-connected layers. A numerical simulation study was performed for multiple damage detection in the hangers using ambient wind vibration data on the bridge deck. The results show that the current CNN using FAS data performs better under various damage states than the CNN using time-history data and the traditional neural network using FAS. Robustness of the present CNN has been proven under various observational noise levels and wind speeds.

• Smart Structures and Systems
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• v.11 no.5
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• pp.555-567
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• 2013

An Remote Corrosion Monitoring (RCM) system consists of an anode with low potential, the metallic structures against corrosion, an electrode to provide reference potential, and a data-acquisition system to ensure the potential difference for anticorrosion. In more detail, the data-acquisition (DAQ) system monitors the potential difference between the metallic structures and a reference electrode to identify the correct potential level against the corrosion of the infrastructures. Then, the measured data are transmitted to a central office to remotely keep track of the status of the corrosion monitoring (CM) system. To date, the RCM system is designed to achieve low power consumption, so that it can be simply powered by batteries. However, due to memory effect and the limited number of recharge cycles, it can entail the maintenance fee or sometimes cause failure to protect the metallic structures. To address this issue, the low-overhead energy harvesting circuitry for the RCM systems has designed to replenish energy storage elements (ESEs) along with redeeming the leakage of supercapacitors. Our developed energy harvester can scavenge the ambient energy from the corrosion monitoring environments and store it as useful electrical energy for powering local data-acquisition systems. In particular, this paper considers the energy harvesting from potential difference due to galvanic corrosion between a metallic infrastructure and a permanent copper/copper sulfate reference electrode. In addition, supercapacitors are adopted as an ESE to compensate for or overcome the limitations of batteries. Experimental results show that our proposed harvesting schemes significantly reduce the overhead of the charging circuitry, which enable fully charging up to a 350-F supercapacitor under the low corrosion power of 3 mW (i.e., 1 V/3 mA).

• Journal of Korean Society of Disaster and Security
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• v.7 no.2
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• pp.1-8
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• 2014

Smart Pole Measurement System was constructed with not only the core sensors of a GNSS receiver, a TRS sensor and a soil moisture sensor but supplementary installation of power supply and radio communication for monitoring steep slope sites. Also a data processing software for displacement extraction and visualization was developed. Smart Pole Measurement sensor is composed of a GNSS antenna at the top of the pole, a TRS sensor and a gyro sensor vertical below right of the antenna and a soil moisture sensor at the bottom of the pole. The sensor combination extracts not only ground combination in real time but transltion, slide, settlement and soil moisture content. This measuring/monitoring system which cosists of data receiving part, data collection/transfer part and data processing part was built to exercise their functions and then test measuring/monitoring was conducted by introducing artificial displacement and the results were analyzed to evaluate field applicability.