A framework is proposed to characterize and forecast the displacement trends of slow-moving landslides, defined as the reactivation stage of phenomena in rocks or fine-grained soils, with movements localized along one...A framework is proposed to characterize and forecast the displacement trends of slow-moving landslides, defined as the reactivation stage of phenomena in rocks or fine-grained soils, with movements localized along one or several existing shear surfaces. The framework is developed based on a thorough analysis of the scientific literature and with reference to significant reported case studies for which a consistent dataset of continuous displacement measurements is available. Three distinct trends of movement are defined to characterize the kinematic behavior of the active stages of slow-moving landslides in a velocity-time plot: a linear trend-type I, which is appropriate for stationary phenomena; a convex shaped trend-type II, which is associated with rapid increases in pore water pressure due to rainfall, followed by a slow decrease in the groundwater level with time; and a concave shaped trend-type III, which denotes a non-stationary process related to the presence of new boundary conditions such as those associated with the development of a newly formed local slip surface that connects with the main existing slip surface. Within the proposed framework, a model is developed to forecast future displacements for active stages of trend-type II based on displacement measurements at the beginning of the stage. The proposed model is validated by application to two case studies.展开更多
Purpose： The purpose of this study was to determine the extent that a static stretching program could increase heart rate （HR） and oxygen consumption （VO2）, and if the increases were sufficient to serve as a warm...Purpose： The purpose of this study was to determine the extent that a static stretching program could increase heart rate （HR） and oxygen consumption （VO2）, and if the increases were sufficient to serve as a warm-up for aerobic activity. Methods： The HR and VO2 of 15 male and 16 female college students were measured after either 12 min of passive static stretching （SS）, or 12 rain pseudo-stretching （PS）, which consisted of moving through the stretching positions without placing the muscles on stretch. Four different lower body stretches were used with each stretch held for 30 s before the participant moved to a different position, with the circuit being repeated four times. VO2 was determined by averaging breath-by-breath measures over the total 12 min. HR was obtained every 30 s and the 24 values were averaged. Warm-up benefit was determined from the 02 deficit accrued during 7-min cycling at 60% VOzmax. Results： HR （beats/rain, mean 4. SD） for SS （84 ± 11） was a significant （p 〈 0.05） 9% greater than PS （78 ± 12）. Similarly, VO2 （mL/min, mean 4. SD） for SS （0.53 ± 0.13） was a significant 44% greater than PS （0.38 ± 0.11）. The O2 deficit （L, mean 4, SD） for SS （0.64 ± 1.54） was not different from PS （0.72 ± 1.61）. Conclusion： These data indicate that passive static stretching increases both HR and VO2, indicating that metabolic activity can be increased without muscle activation. The magnitude of the increases, however, is not sufficient to elicit a warm-up effect.展开更多
Support Vector Machine (SVM) is a powerful methodology for solving problems in non-linear classification, function estimation and density estimation, which has also led to many other recent developments in kernel base...Support Vector Machine (SVM) is a powerful methodology for solving problems in non-linear classification, function estimation and density estimation, which has also led to many other recent developments in kernel based methods in general. This paper presents a highaccuracy and fault-tolerant SVM for the mobile geo-location problem, which is an important component of pervasive computing. Simulation results show its basic location performance, and illustrate impacts of the number of training samples and training area on test location error.展开更多
This paper proposes a precise localization algorithm for a quickly moving mobile robot.In order to localize a mobile robot with active beacon sensors,a relatively long time is needed,since the distance to the beacon i...This paper proposes a precise localization algorithm for a quickly moving mobile robot.In order to localize a mobile robot with active beacon sensors,a relatively long time is needed,since the distance to the beacon is measured by transmitting time of the ultrasonic signal.The measurement time does not cause a high error rate when the mobile robot moves slowly.However,with an increase of the mobile robot’s speed,the localization error becomes too high to use for accurate mobile robot navigation.Therefore,in this research into high speed mobile robot operations,instead of using two active beacons for localization,an active beacon and dual compass are utilized to localize the mobile robot.This new approach resolves the high localization error caused by the speed of the mobile robot.The performance of the precise localization algorithm is verified by comparing it to the conventional method through real-world experiments.展开更多
基金partially supported by the University of Salerno (Italy) through the Civil and Environmental Engineering Ph.D. programme and FARB research funding
文摘A framework is proposed to characterize and forecast the displacement trends of slow-moving landslides, defined as the reactivation stage of phenomena in rocks or fine-grained soils, with movements localized along one or several existing shear surfaces. The framework is developed based on a thorough analysis of the scientific literature and with reference to significant reported case studies for which a consistent dataset of continuous displacement measurements is available. Three distinct trends of movement are defined to characterize the kinematic behavior of the active stages of slow-moving landslides in a velocity-time plot: a linear trend-type I, which is appropriate for stationary phenomena; a convex shaped trend-type II, which is associated with rapid increases in pore water pressure due to rainfall, followed by a slow decrease in the groundwater level with time; and a concave shaped trend-type III, which denotes a non-stationary process related to the presence of new boundary conditions such as those associated with the development of a newly formed local slip surface that connects with the main existing slip surface. Within the proposed framework, a model is developed to forecast future displacements for active stages of trend-type II based on displacement measurements at the beginning of the stage. The proposed model is validated by application to two case studies.
文摘Purpose： The purpose of this study was to determine the extent that a static stretching program could increase heart rate （HR） and oxygen consumption （VO2）, and if the increases were sufficient to serve as a warm-up for aerobic activity. Methods： The HR and VO2 of 15 male and 16 female college students were measured after either 12 min of passive static stretching （SS）, or 12 rain pseudo-stretching （PS）, which consisted of moving through the stretching positions without placing the muscles on stretch. Four different lower body stretches were used with each stretch held for 30 s before the participant moved to a different position, with the circuit being repeated four times. VO2 was determined by averaging breath-by-breath measures over the total 12 min. HR was obtained every 30 s and the 24 values were averaged. Warm-up benefit was determined from the 02 deficit accrued during 7-min cycling at 60% VOzmax. Results： HR （beats/rain, mean 4. SD） for SS （84 ± 11） was a significant （p 〈 0.05） 9% greater than PS （78 ± 12）. Similarly, VO2 （mL/min, mean 4. SD） for SS （0.53 ± 0.13） was a significant 44% greater than PS （0.38 ± 0.11）. The O2 deficit （L, mean 4, SD） for SS （0.64 ± 1.54） was not different from PS （0.72 ± 1.61）. Conclusion： These data indicate that passive static stretching increases both HR and VO2, indicating that metabolic activity can be increased without muscle activation. The magnitude of the increases, however, is not sufficient to elicit a warm-up effect.
文摘Support Vector Machine (SVM) is a powerful methodology for solving problems in non-linear classification, function estimation and density estimation, which has also led to many other recent developments in kernel based methods in general. This paper presents a highaccuracy and fault-tolerant SVM for the mobile geo-location problem, which is an important component of pervasive computing. Simulation results show its basic location performance, and illustrate impacts of the number of training samples and training area on test location error.
基金supported by the MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2011-C1090-1121-0010)
文摘This paper proposes a precise localization algorithm for a quickly moving mobile robot.In order to localize a mobile robot with active beacon sensors,a relatively long time is needed,since the distance to the beacon is measured by transmitting time of the ultrasonic signal.The measurement time does not cause a high error rate when the mobile robot moves slowly.However,with an increase of the mobile robot’s speed,the localization error becomes too high to use for accurate mobile robot navigation.Therefore,in this research into high speed mobile robot operations,instead of using two active beacons for localization,an active beacon and dual compass are utilized to localize the mobile robot.This new approach resolves the high localization error caused by the speed of the mobile robot.The performance of the precise localization algorithm is verified by comparing it to the conventional method through real-world experiments.
