• The Journal of Advanced Prosthodontics
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• v.8 no.6
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• pp.417-422
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• 2016

PURPOSE. The purposes of this study were to evaluate the staining resistance of CAD/CAM resin-ceramics polished with different techniques and to determine the effectiveness of the polishing techniques on resin-ceramics, comparing it with that of a glazed glass-ceramic. MATERIALS AND METHODS. Four different CAD/CAM ceramics (feldspathic ceramic: C-CEREC Blocs, (SIRONA) and three resin-ceramics: L-Lava Ultimate, (3M ESPE), E-Enamic, (VITA) and CS-CeraSmart, (GC)) and one light cure composite resin: ME-Clearfil Majesty Esthetic (Kuraray) were used. Only C samples were glazed (gl). Other restorations were divided into four groups according to the polishing technique: nonpolished control group (c), a group polished with light cure liquid polish (Biscover LV BISCO) (bb), a group polished with ceramic polishing kit (Diapol, EVE) (cd), and a group polished with composite polishing kit (Clearfil Twist Dia, Kuraray) (kc). Glazed C samples and the polished samples were further divided into four subgroups and immersed into different solutions: distilled water, tea, coffee, and fermented black carrot juice. Eight samples ($8{\times}8{\times}1mm$) were prepared for each subgroup. According to CIELab system, four color measurements were made: before immersion, immersion after 1 day, after 1 week, and after 1 month. Data were analyzed with repeated measures of ANOVA (${\alpha}=.05$). RESULTS. The highest staining resistance was found in gl samples. There was no difference among gl, kc and cd (P>.05). Staining resistance of gl was significantly higher than that of bb (P<.05). Staining resistances of E and CS were significantly higher than those of L and ME (P<.05). CONCLUSION. Ceramic and composite polishing kits can be used for resin ceramics as a counterpart of glazing procedure used for full ceramic materials. Liquid polish has limited indications for resin ceramics.

• Journal of the Korean Society of Costume
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• v.56 no.9 s.109
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• pp.1-13
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• 2006

The purpose of this study is to apply a concept of open structure to clothing design and to verify the characteristics found in the various types of clothing which has open structure. The literatures from various academic fields including philosophy, literature, social science, architecture, and fine arts are investigated to define the concept of openness and to analyze it from the perspectives both of the visual and of the moaning of openness. This paper is to identify the types and the characteristics of clothing by future intention, complexity, discontinuity of open structure. By closely examining fashion design after 1980s found in fashion collection publications and designer's websites, the results of this study are as follows: first, the concept of openness can be classified into two different levels, that is, visual and meaning, secondly, in clothing the concept of open structure is applied to the meaning side by future intention, by complexity and by discontinuity. Open structure through future Intention has new content and interpretation and must have the possibility of intelligence awakening, future guidance and basic contents. Open structure through complexity has secondary function exists concurrent with the shape key example is the smart clothes with the digital functions. It has functions of amusement, supplement and protective, and is future clothes which satisfies with health, welfare, desire of beauty. Open structure with discontinuity is clothes with dramatic changes in system, structures and states. Structure can be changed by silhouette, detail, or fabric, material, or dramatic and practical function as tools in terms of productions and environment. This study can help to formulate and to integrate the concept of open structure in clothing with various phases and enhance the value of clothes by showing an application of the concept of openness to the clothing in meaning level.

• Smart Structures and Systems
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• v.6 no.3
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• pp.225-238
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• 2010

We report on the development of a new technology for the fabrication of Micro-Electro-Mechanical-System (MEMS) strain sensors to realize a novel type of crackmeter for health monitoring of ageing civil infrastructures. The fabrication of micromachined silicon MEMS sensors based on a Silicon On Insulator (SOI) technology, designed according to a Double Ended Tuning Fork (DETF) geometry is presented, using a novel process which includes a gap narrowing procedure suitable to fabricate sensors with low motional resistance. In order to employ these sensors for crack monitoring, techniques suited for bonding the MEMS sensors on a steel surface ensuring good strain transfer from steel to silicon and a packaging technique for the bonded sensors are proposed, conceived for realizing a low-power crackmeter for ageing infrastructure monitoring. Moreover, the design of a possible crackmeter geometry suited for detection of crack contraction and expansion with a resolution of $10{\mu}m$ and very low power consumption requirements (potentially suitable for wireless operation) is presented. In these sensors, the small crackmeter range for the first field use is related to long-term observation on existing cracks in underground tunnel test sections.

• Smart Structures and Systems
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• v.6 no.3
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• pp.183-196
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• 2010

Monitoring and economical design of alternative energy generators such as wind turbines is becoming increasingly critical; however acquisition of the dynamic output data can be a time-consuming and costly process. In recent years, low-cost wireless sensors have emerged as an enabling technology for structural monitoring applications. In this study, wireless sensor networks are installed in three operational turbines in order to demonstrate their efficacy in this unique operational environment. The objectives of the first installation are to verify that vibrational (acceleration) data can be collected and transmitted within a turbine tower and that it is comparable to data collected using a traditional tethered system. In the second instrumentation, the wireless network includes strain gauges at the base of the structure. Also, data is collected regarding the performance of the wireless communication channels within the tower. In both turbines, collected wireless sensor data is used for off-line, output-only modal analysis of the ambiently (wind) excited turbine towers. The final installation is on a turbine with embedded braking capabilities within the nacelle to generate an "impulse-like" load at the top of the tower. This ability to apply such a load improves the modal analysis results obtained in cases where ambient excitation fails to be sufficiently broad-band or white. The improved loading allows for computation of true mode shapes, a necessary precursor to many conditional monitoring techniques.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1107-1127
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• 2016

Studies on dynamic characteristics of the hanger vibration using field monitoring data are important for the design and evaluation of high-speed railway truss arch bridges. This paper presents an analysis of the hanger's dynamic displacement responses based on field monitoring of Dashengguan Yangtze River Bridge, which is a high-speed railway truss arch bridge with the longest span throughout the world. The three vibration parameters, i.e., dynamic displacement amplitude, dynamic load factor and vibration amplitude, are selected to investigate the hanger's vibration characteristics in each railway load case including the probability statistical characteristics and coupled vibration characteristics. The influences of carriageway and carriage number on the hanger's vibration characteristics are further investigated. The results indicate that: (1) All the eight railway load cases can be successfully identified according to the relationship of responses from strain sensors and accelerometers in the structural health monitoring system. (2) The hanger's three vibration parameters in each load case in the longitudinal and transverse directions have obvious probabilistic characteristics. However, they fall into different distribution functions. (3) There is good correlation between the hanger's longitudinal/transverse dynamic displacement and the main girder's transverse dynamic displacement in each load case, and their relationships are shown in the hysteresis curves. (4) Influences of the carriageway and carriage number on the hanger's three parameters are different in both longitudinal and transverse directions; while the influence on any of the three parameters presents an obvious statistical trend. The present paper lays a good foundation for the further analysis of train-induced hanger vibration and control.

• Smart Structures and Systems
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• v.17 no.2
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• pp.209-230
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• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.

• Smart Structures and Systems
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• v.15 no.3
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• pp.665-682
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• 2015

Structural identification or St-Id is 'the parametric correlation of structural response characteristics predicted by a mathematical model with analogous characteristics derived from experimental measurements'. This paper describes a St-Id exercise on Humber Bridge that adopted a novel two-stage approach to first calibrate and then validate a mathematical model. This model was then used to predict effects of wind and temperature loads on global static deformation that would be practically impossible to observe. The first stage of the process was an ambient vibration survey in 2008 that used operational modal analysis to estimate a set of modes classified as vertical, torsional or lateral. In the more recent second stage a finite element model (FEM) was developed with an appropriate level of refinement to provide a corresponding set of modal properties. A series of manual adjustments to modal parameters such as cable tension and bearing stiffness resulted in a FEM that produced excellent correspondence for vertical and torsional modes, along with correspondence for the lower frequency lateral modes. In the third stage traffic, wind and temperature data along with deformation measurements from a sparse structural health monitoring system installed in 2011 were compared with equivalent predictions from the partially validated FEM. The match of static response between FEM and SHM data proved good enough for the FEM to be used to predict the un-measurable global deformed shape of the bridge due to vehicle and temperature effects but the FEM had limited capability to reproduce static effects of wind. In addition the FEM was used to show internal forces due to a heavy vehicle to to estimate the worst-case bearing movements under extreme combinations of wind, traffic and temperature loads. The paper shows that in this case, but with limitations, such a two-stage FEM calibration/validation process can be an effective tool for performance prognosis.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• Smart Structures and Systems
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• v.22 no.4
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• pp.481-493
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• 2018

Ultrasonic guided waves have attracted increasing attention for non-destructive testing (NDT) and structural health monitoring (SHM) of bridge cables. They offer advantages like single measurement, wide coverage of acoustical field, and long-range propagation capability. To design defect detection systems, it is essential to understand how guided waves propagate in cables and how to select the optimal excitation frequency and mode. However, certain cable characteristics such as multiple wires, anchorage, and polyethylene (PE) sheath increase the complexity in analyzing the guided wave propagation. In this study, guided wave modes for multi-wire bridge cables are identified by using a semi-analytical finite element (SAFE) technique to obtain relevant dispersion curves. Numerical results indicated that the number of guided wave modes increases, the length of the flat region with a low frequency of L(0,1) mode becomes shorter, and the cutoff frequency for high order longitudinal wave modes becomes lower, as the number of steel wires in a cable increases. These findings were used in design of transducers for defect detection and selection of the optimal wave mode and frequency for subsequent experiments. A magnetostrictive transducer system was used to excite and detect the guided waves. The applicability of the proposed approach for detecting and locating wire breakages was demonstrated for a cable with 37 wires. The present ultrasonic guided wave method has been found to be very responsive to the number of brokenwires and is thus capable of detecting defects with varying sizes.

• Physical Therapy Rehabilitation Science
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• v.9 no.2
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• pp.105-112
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• 2020

Objective: To investigate the effects of training using a trunk control robot (TCR) system combined with conventional therapy (CT) on balance and gait abilities in persons with chronic stroke. Design: Two-group pretest-posttest design. Methods: Thirty-five subjects with chronic stroke were randomly assigned to either the TCR group (n=17) or the trunk extension-training (TET) group (n=18). Both groups performed CT for 30 minutes, after which the TCR group performed TCR training and the TET group performed trunk extension training for 20 minutes. Both groups performed the therapeutic interventions 3 days per week for 6 weeks. Balance ability was evaluated using the Berg Balance Scale (BBS), and the Timed Up-and-Go (TUG) test. Gait ability was measured using the 10 m Walk Test (10MWT) and the NeuroCom Smart Balance Master. Results: TCR group showed significant improvements in static balance (weight bearing) and dynamic balance (weight shifting speed, weight shifting direction, BBS, and TUG), 10MWT, gait speed, and step width (p<0.05); step length was not significant. The TET group showed a significant partial improvement of dynamic balance (weight shifting speed, weight shifting direction, BBS, and 10MWT (p<0.05), but the improvements in static balance, TUG, gait speed, and step width and step length was not significant. Additionally, significant differences in static balance, dynamic balance (weight shifting speed, weight shifting direction, BBS, and TUG), 10MWT, gait speed, and step width were detected between groups (p<0.05). Conclusions: TCR training combined with CT is effective in improving static and dynamic balance, as well as gait abilities in persons with chronic stroke.