• Physical Therapy Korea
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• v.21 no.3
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• pp.80-88
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• 2014

Previous studies have reported that decreased cognitive ability has been consistently associated with significant declines in performance of one or both tasks under a dual-task walking condition. This study examined the relationship between specific cognitive abilities and the dual-task costs (DTCs) of spatio-temporal gait parameters in stroke patients. The spatio-temporal gait parameters were measured among 30 stroke patients while walking with and without a cognitive task (Stroop Word-Color Task) at the study participant's preferred walking speed. Cognitive abilities were measured using Computerized Neuropsychological Testing. Pearson's correlation coefficients (r) were calculated to quantify the associations between the neuropsychological measures and the DTCs in the spatio-temporal gait parameters. Moderate to strong correlations were found between the Auditory Continuous Performance test (ACPT) and the DTCs of the Single Support Time of Non-paretic (r=.37), the Trail Making A (TMA) test and the DTCs of Velocity (r=.71), TMA test and the DTCs of the Step Length of Paretic (r=.37), TMA test and the DTCs of the Step Length Non-paretic (r=.36), the Trail Making B (TMB) test and the DTCs of Velocity (r=.70), the Stroop Word-Color test and the DTCs of Velocity (r=-.40), Visual-span Backward (V-span B) test and the DTCs of Velocity (r=-.41), V-span B test and the DTCs of the Double Support Time of Non-paretic (r=.38), Digit-span Forward test and the DTCs of the Step Time of Non-paretic (r=-.39), and Digit-span Backward test and the DTCs of the Single Support Time of Paretic (r=.36). Especially TMA test and TMB test were found to be more strongly correlated to the DTCs of gait velocity than the other correlations. Understanding these cognitive features will provide guidance for identifying dual- task walking ability.

• Earthquakes and Structures
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• v.8 no.4
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• pp.859-887
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• 2015

Structural health monitoring (SHM) has gained in popularity in recent years since it can assess the performance and condition of instrumented structures in real time and provide valuable information to the asset's manager and owner. Operational modal analysis plays an important role in SHM and it involves the determination of natural frequencies, damping ratios and mode shapes of a constructed structure based on measured dynamic data. This paper presents the operational modal analysis and seismic response characterization of the Tsing Ma Suspension Bridge of 2,160 m long subjected to different earthquake events. Three kinds of events, i.e., short-distance, middle-distance and long-distance earthquakes are taken into account. A fast Bayesian modal identification method is used to carry out the operational modal analysis. The modal properties of the bridge are identified and compared by use of the field monitoring data acquired before and after the earthquake for each type of the events. Research emphasis is given on identifying the predominant modes of the seismic responses in the deck during short-distance, middle-distance and long-distance earthquakes, respectively, and characterizing the response pattern of various structural portions (deck, towers, main cables, etc.) under different types of earthquakes. Since the bridge is over 2,000 m long, the seismic wave would arrive at the tower/anchorage basements of the two side spans at different time instants. The behaviors of structural dynamic responses on the Tsing Yi side span and on the Ma Wan side span under each type of the earthquake events are compared. The results obtained from this study would be beneficial to the seismic design of future long-span bridges to be built around Hong Kong (e.g., the Hong Kong-Zhuhai-Macau Bridge).

• Journal of Preventive Medicine and Public Health
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• v.27 no.3 s.47
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• pp.487-504
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• 1994

A cross-sectional study was performed to evaluate the effects of chronic low-dose solvent on neurobehavioral performance of 118 male car painters. A control group of 113 workers matched for age was selected from different sections of the factory. The mean age and the mean duration of employment were 33 years and 6.7 years in both groups. Mean years of education were 11.4 years in car painters and 11.8 years in controls. Each worker completed a medical and occupational questionnaire and four tests of Swedish performance evaluation system. These included simple reaction time, symbol digit, digit span and finger tapping speed. Althougth the mean duration of employment was 6.7 years, comparison of mean performance showed a significantly poorer performance on simple reaction time (p<0.05), symbol digit(p<0.01) and digit span(p<0.05) in car painters. In univariate analysis, age and educational level contributed to poorer performance on symbol digit and digit span. Smoking appeared to slow finger tapping speed in car painters. Performance of four tests of car painters exposed to high level of solvent was poorer than that of car painters exposed to low level. In multiple regression models, controlling for age, alcohol, smoking and shift work, solvent exposure was found to be associated with performance of simple reaction time, symbol digit and digit span and exposure to high level of solvent was related to poorer performance of symbol digit and digit span.

• Journal of Korean society of Dental Hygiene
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• v.11 no.6
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• pp.939-949
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• 2011

Objectives : The purpose of this study was to examine the job awareness of dental hygiene students about a dental hygienist, what duties they wanted to do as dental hygienists, their awareness of college courses related to the job performance of dental hygienists and whether they viewed the courses as what's most widely utilized for the clinical job performance of dental hygienists. It's ultimately meant to help provide good education for dental hygiene students to have the right understanding of dental hygienists and bolster their professionalism. Methods : The subjects in this study were 301 dental hygiene students in four different colleges located in the metropolitan area. A survey was conducted to find out their satisfaction level with the department of dental hygiene, personal characteristics, awareness of college courses and awareness of the duties of dental hygienists. Results : The group of students who deemed the life span of the dental hygienist occupation to be long put more significance on the college courses that should focus on job performance. As for the relationship between their personal characteristics and awareness of the college courses, their satisfaction or dissatisfaction with the department and their ideas on the life span of the occupation made significant differences to that. The group of students who considered the life span of the occupation to be longer thought that the college courses would be more linked to the duties of dental hygienists and their job performance and should be given more weight, and there were significant differences among them in their view of the life span of the occupation and awareness of the college courses that should be given more weight(p<.05). Their view of how much the college courses would be linked to the duties of dental hygienists had a statistically significant correlation to that of the college courses that should focus on the clinical job performance of dental hygienists. Conclusions : The above-mentioned findings suggest that as part of the regular curriculum, the kind of education that aims at boosting the professionalism and job performance of dental hygienists as experts should be provided for dental hygiene students to build the right values as professional dental hygienists.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.159-166
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• 2006

Although the strain distribution along the length of a beam in buildings or infrastructures is non-uniform, most fiber optic sensors are point sensors that can measure the strain only at a local point of a beam. Long gage fiber optic sensors that measure integrated strain over a relatively long length can consider strain variation. This type of sensor was found to be efficient and useful for monitoring large-scale structures. On the other hand, the maximum strain or stress in a beam can not be measured with long gage optic sensors. However, for the assessment of the safety of multi-span steel beams subjected to various vertical loads, the maximum strain or stress measured during monitoring is required for comparison with the allowable stress of the beam calculated by a design code. Therefore, in this paper, mathematical models are presented for determination of the maximum values of strains in more three-span steel beams based on the average strains measured by long gage optic sensors.

• Structural Engineering and Mechanics
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• v.74 no.2
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• pp.157-173
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• 2020

In the finite element modelling of long-span cable-stayed bridges, there are a lot of uncertainties brought about by the complex structural configuration, material behaviour, boundary conditions, structural connections, etc. In order to reduce the discrepancies between the theoretical finite element model and the actual static and dynamic behaviour, updating is indispensable after establishment of the finite element model to provide a reliable baseline version for further analysis. Traditional sensitivity-based updating methods cannot support updating based on static and dynamic measurement data at the same time. The finite element model is required in every optimization iteration which limits the efficiency greatly. A convenient but accurate Kriging surrogate model for updating of the finite element model of cable-stayed bridge is proposed. First, a simple cable-stayed bridge is used to verify the method and the updating results of Kriging model are compared with those using the response surface model. Results show that Kriging model has higher accuracy than the response surface model. Then the method is utilized to update the model of a long-span cable-stayed bridge in Hong Kong. The natural frequencies are extracted using various methods from the ambient data collected by the Wind and Structural Health Monitoring System installed on the bridge. The maximum deflection records at two specific locations in the load test form the updating objective function. Finally, the fatigue lives of the structure at two cross sections are calculated with the finite element models before and after updating considering the mean stress effect. Results are compared with those calculated from the strain gauge data for verification.

• Journal of Technologic Dentistry
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• v.28 no.2
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• pp.321-329
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• 2006

The popularity of Ni-Cr-Mo based metal alloys for metal-ceramic crown have increased recently because of low price, superior yield strength and rigidity. the use of these alloys give them the potential advantage of thinner copping with the required rigidity for long span bridges. The purpose of this study was to assess the microstructures and mechanical properties of Ni-Cr-Mo-(Si,Al,Nb,Zr,Ti.Cu,Mm) based Alloys not containing beryllium(Be) related toxic effects. The abtained results indicated that as-cast these specimen alloys showed compositional and microstructural differences, and mechanical properties values of Ni69Cr20Mo5Si2Al4 alloy among these specimen alloys was found to be superior to those of commercial Ni-Cr based alloy using in market place today.

• Smart Structures and Systems
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• v.31 no.2
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• pp.183-197
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• 2023

For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.

• Smart Structures and Systems
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• v.29 no.1
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• pp.93-103
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• 2022

With the wider availability of sensor technology through easily affordable sensor devices, several Structural Health Monitoring (SHM) systems are deployed to monitor vital civil infrastructure. The continuous monitoring provides valuable information about the health of the structure that can help provide a decision support system for retrofits and other structural modifications. However, when the sensors are exposed to harsh environmental conditions, the data measured by the SHM systems tend to be affected by multiple anomalies caused by faulty or broken sensors. Given a deluge of high-dimensional data collected continuously over time, research into using machine learning methods to detect anomalies are a topic of great interest to the SHM community. This paper contributes to this effort by proposing a relatively new time series representation named "Shapelet Transform" in combination with a Random Forest classifier to autonomously identify anomalies in SHM data. The shapelet transform is a unique time series representation based solely on the shape of the time series data. Considering the individual characteristics unique to every anomaly, the application of this transform yields a new shape-based feature representation that can be combined with any standard machine learning algorithm to detect anomalous data with no manual intervention. For the present study, the anomaly detection framework consists of three steps: identifying unique shapes from anomalous data, using these shapes to transform the SHM data into a local-shape space and training machine learning algorithms on this transformed data to identify anomalies. The efficacy of this method is demonstrated by the identification of anomalies in acceleration data from an SHM system installed on a long-span bridge in China. The results show that multiple data anomalies in SHM data can be automatically detected with high accuracy using the proposed method.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.53-56
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• 2007

It was previously introduced a new displacement measuring technique using terrestrial laser scanning (TLS) that remotely samples the surface of an object using laser pulses and generates the three-dimensional (3D) coordinates of numerous points on the surface. In this paper, for an assessment of the capabilities of the measuring technique about existing structures, the field tests for vertical displacement measurement of an existing long span steel box-girder are experimentally carried out. The performance of the technique is evaluated by comparing the displacements obtained from TLS system and displacements directly measured from linear variable displacement transducer (LVDT).