• 한국환경과학회지
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• 제32권10호
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• pp.693-701
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• 2023

In this study, we analyzed 82 dust damage dispute mediation cases over the past 5 years and evaluated cases where the probability of damage was verified through dust concentration measurement, modeling prediction, and chemical composition analysis. The cause of dust damage was a construction site, which accounted for most of the damage (97%), and was closely related to the distance from the construction site, total floor area of the construction site, and construction duration. Compensation was decided in only 33% of dust damage cases, and in only 6% (five cases) were damages determined using scientific techniques such as dust measurement, and forecasting. The main criteria for determining compensation were whether administrative measures were taken and evidence of damage in the form of videos and photos. In the future, measuring or model for the amount of dust damage is necessary to determine whether the limit has been exceeded and to revise the standard for calculating compensation through various lines of evidence of dust damage.

• 비파괴검사학회지
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• 제34권6호
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• pp.447-456
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• 2014

In this paper, a new damage-detection method based on structural vibration is proposed. The essence of the proposed method is the detection of abrupt changes in rotation. Damage-induced rotation (DIR), which is determined from the modal flexibility of the structure, initially occurs only at a specific damaged location. Therefore, damage can be localized by evaluating abrupt changes in rotation. We conducted numerical simulations of two damage scenarios using a 10-story cantilever-type building model. Measurement noise was also considered in the simulation. We compared the sensitivity of the proposed method to localize damage to that of two conventional modal-flexibility-based damage-detection methods, i.e., uniform load surface (ULS) and ULS curvature. The proposed method was able to localize damage in both damage scenarios for cantilever structures, but the conventional methods could not.

• Structural Monitoring and Maintenance
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• 제9권2호
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• Journal of Preventive Medicine and Public Health
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• 제36권3호
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• pp.230-238
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• 2003

Objectives : To estimate the value of statistical life (VSL) and health damage cost on theoretical mortality estimates due to environmental pollution. Methods : We assessed the health risk on three environmental problems and eight sub-problems. Willingness to pay (WTP) was elucidated from a questionnaire survey with dichotomous contingent valuation method and VSL (which is the division of WTP by the change of risk reduction) calculated from WTP. Damage costs were estimated by multiplying VSL by the theoretical mortality estimates. Results : VSLs from death caused by air pollution, indoor air pollution and drinking water contamination were about 0.3, 0.5 and 0.3 billion won, respectively. Damage costs of particulate matters ($PM_{10}$) and radon were higher in the sub-problems and were above 100 billion won. Because damage cost depends on theoretical mortality estimate and WTP, its uncertainty is reduced in the estimating process. Conclusion : Health damage cost or risk benefit should be considered as one scientific criterion for decision making in environmental policy.

• 한국환경성돌연변이발암원학회지
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• 제22권2호
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• pp.83-89
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• 2002

The single cell gel electrophoresis (comet) assay is one of the useful tools for the study of genetic damage in humans exposed to environmental mutagens and carcinogens. This study was undertaken to evaluate the status of DNA damage in peripheral lymphocytes depending on their sex, age, smoking habits, and other factors in normal healthy Korean population. The 99 volunteers included in the study and out of these, 36 volunteers were smoker and 63 volunteers were non-smoker aged between 20-59 years. All individual answered a questionnaire that assessed their general information including smoking habits and the extent of the environmental tobacco smoke (ETS) exposure, and blood samples were obtained. There was a statistically significant difference in the extent of DNA damage between smoker and non-smoker (p<0.001). A significant difference was also observed between male and female (p<0.001) and amongst the different group of age (p<0.005), however, correlation analysis showed that only smoking habit was a significant factor for DNA damage. No significant effect of smoking duration, number of cigarettes smoking a day, SPY (smoke pack years) in smokers and environmental tobacco smoke exposure in non-smokers on the status of DNA damage was observed.

• 한국환경보건학회지
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• 제47권5호
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• pp.379-383
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• 2021

This paper discussed environmental health policies for the past and coming decade by reviewing the First Comprehensive Environmental Health Plan (2011~2020) and introducing the Second Comprehensive Environmental Health Plan (2021~2030). The major achievement of the First Comprehensive Environmental Health Plan was the establishment of receptor-oriented environmental health policies. However, the main limitations were insufficient policy support for relief and/or recovery from environmental pollution damage and low public awareness of environmental health policies. The Second Comprehensive Environmental Health Plan presents the following major policy tasks: establish an omnidirectional environment health investigation and monitoring system, provide customized environmental health services, improve the environmental health damage relief and recovery system, and promote regional environmental health policies. The Second Plan has a clear distinction from the First Plan in that it expands the field of environmental health from the prevention and management of environmental risk factors to proactive damage response and recovery, which will effectively contribute to alleviating the burden of environmental disease.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.505-509
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• 2020

Twitter is a useful medium to grasp various damage situations that have occurred in society. However, it is a laborious task to spot damage-related topics according to time in the environment where information is constantly produced. This paper proposes a methodology of constructing a knowledge structure by combining the BERT-based classifier and the community detection techniques to discover the topics underlain in the damage information. The methodology consists of two steps. In the first step, the tweets are classified into the classes that are related to human damage, infrastructure damage, and industrial activity damage by a BERT-based transfer learning approach. In the second step, networks of the words that appear in the damage-related tweets are constructed based on the co-occurrence matrix. The derived networks are partitioned by maximizing the modularity to reveal the hidden topics. Five keywords with high values of degree centrality are selected to interpret the topics. The proposed methodology is validated with the Hurricane Harvey test data.

• Structural Monitoring and Maintenance
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• 제7권2호
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• pp.149-166
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• 2020

This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.

• Structural Monitoring and Maintenance
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• 제6권3호
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Smart Structures and Systems
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• 제5권1호
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• pp.95-117
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• 2009

In this paper, the time series based damage detection algorithms developed by Nair, et al. (2006) and Nair and Kiremidjian (2007) are applied to the benchmark experimental data from the National Center for Research on Earthquake Engineering (NCREE) in Taipei, Taiwan. Both acceleration and strain data are analyzed. The data are modeled as autoregressive (AR) processes, and damage sensitive features (DSF) and feature vectors are defined in terms of the first three AR coefficients. In the first algorithm developed by Nair, et al. (2006), hypothesis tests using the t-statistic are applied to evaluate the damaged state. A damage measure (DM) is defined to measure the damage extent. The results show that the DSF's from the acceleration data can detect damage while the DSF from the strain data can be used to localize the damage. The DM can be used for damage quantification. In the second algorithm developed by Nair and Kiremidjian (2007) a Gaussian Mixture Model (GMM) is used to model the feature vector, and the Mahalanobis distance is defined to measure damage extent. Additional distance measures are defined and applied in this paper to quantify damage. The results show that damage measures can be used to detect, quantify, and localize the damage for the high intensity and the bidirectional loading cases.