• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.110-122
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• 2014

Korea's film industry has been growing over the last 10 years, and there has been much attention to the antecedents of film box office sales both academic and business communities. So far, previous research which explained success factors of film or movie mainly focused on 3 stages, production, distribution and screening. However, these 3 steps are heavily vertically integrated in Korea's firm industry unlike United States. Almost 130% of movie theaters are multiplex chain and operated by film production companies such as CJ and Lotte Entertainment In this situation, film sales are likely to he affected by movie theaters own facilities or location factors rather than movie contents. Based. on resource-based view and S-C-P paradigm, the authors examined "whether movie theater's facilities factors and trade area factors such as accessibility, competitive situation, and population have effect to movie theater's sales revenues. The results showed that the average occupancy of theater is the most important factor to movie theaters sales in both large and small cities. In large cities, movie theater's facilities factors which included vibration seat special sound system, premium movie theater, VIP lounge are relatively important than trade area factors. In contrast, in small cities, location factors and accessibility are the most important factors to movie theaters sales. We discuss the managerial and theoretical implication for the results and the specific limitations are suggested at the end of the paper.

• Journal of Environmental Health Sciences
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• v.27 no.3
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• pp.71-80
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• 2001

Blood and urine mercury level of three workers were monitored during 60~80 days after high exposure to mercury at the silver refining plant. Mercury was used to form silver-mercury amalgam from plating sludge. Workers were exposed to mercury about 70 days at the several processes, such as hand held weaving, vibration table, and heating from the furnace. mercury was analysed by atomic absorption spectroscopy-vapor generation technique. Recovery from the biological sample was 95.51% and pooled standard deviation was 0.033. At the time of study, there was no work at the workplace. So, airborne mercury concentration was measured with area sampling 5 days after the work, ranged from 0.1459 to 1.2351 mg/㎥(Arithmatic mean 0.4711 mg/㎥, Geometric mean 0.3566 mg/㎥) at the inside of the plant, that is far above the ACGIH's TLV(0.025 mg/㎥) and ranged from 0.0073 to 0.0330 mg/㎥ at the outdoor. Blood mercury levels at the beginning of the monitoring were 4~14 times greater than the American Conference of Governmental Industrial Hygienists Biological Exposure Index(ACGIH BEI, 15 ug/L). Blood mercury levels were decreased logarithmically, that is, rapidly at the high level and slowly at the low level but sustained above the level of the ACGIH BEI 60~80 days after the work. Urine mercury levels at the beginning of the monitoring were 8~16 times greater than the ACGIH BEI(35 ug/g creatinine). Urine mercury levels were decreased logarithmically, but correlation between urine level and off-days were lower than those of blood. Decreasing pattern of blood mercury levels were little affected than that of urine levels when the chelating agent, D-penicillamine, was administered. There was correlation between blood mercury level and urine mercury level(0.81~0.83) but it didn\`t mean that the highest blood mercury level corresponded the highest urine mercury level. In our study, Case 1 always shows the highest level in urine but case 3 always shows the highest level in blood. Creatinine correction represented better correlations between urine mercury levels and blood levels, and between urine levels and off-days rather than by urine volume. Spot urine sampling had a wide variation than that of whole day urine sampling. So, We recommend spot urine sampling for screening and whole day urine sampling for exact diagnosis.