Investigation on parameters used in warning systems for rain-induced embankment instability

A number of instrumented laboratory-scale soil embankment slopes were subjected to artificial rainfall until they failed. The factor of safety of the slope based on real-time measurements of pore-water pressure (suction) and laboratory measured soil properties were calculated as the rainfall progressed. Based on the experiment measurements and slope stability analysis, it was observed that slope displacement measurements can be used to warn the slope failure more accurately. Further, moisture content/pore-water pressure measurements near the toe of the slope and the real-time factor of safety can also be used for prediction of rainfall-induced embankment failures with adequate accuracy.

A method for predicting rain-induced instability of an individual slope

Awareness to avoid losses and casualties due to rain-induced landslide is increasing in regions that routinely experience heavy rainfall. Improvements in early warning systems against rain-induced landslide such as prediction modelling using rainfall records, is urgently needed in vulnerable regions. The existing warning systems have been applied using stability chart development and real-time displacement measurement on slope surfaces. However, there are still some drawbacks such as: ignorance of rain-induced instability mechanism, mislead prediction due to the probabilistic prediction and short time for evacuation. In this research, a real-time predictive method was proposed to alleviate the drawbacks mentioned above. A case-study soil slope in Indonesia that failed in 2010 during rainfall was used to verify the proposed predictive method. Using the results from the field and laboratory characterizations, numerical analyses can be applied to develop a model of unsaturated residual soils slope with deep cracks and subject to rainwater infiltration. Real-time rainfall measurement in the slope and the prediction of future rainfall are needed. By coupling transient seepage and stability analysis, the variation of safety factor of the slope with time were provided as a basis to develop method for the real-time prediction of the rain-induced instability of slopes. This study shows the proposed prediction method has the potential to be used in an early warning system against landslide hazard, since the FOS value and the timing of the end-result of the prediction can be provided before the actual failure of the case study slope.

Best after rain : waterfall discharges and the tourist experience

Waterfalls attract tourists because they are aesthetically appealing landscape features that are not part of everyday experience. It is generally understood that falls are usually seen at their best when there is a copious flow of water, especially after heavy rain. Guidebooks often contain this observation when referring to waterfalls, sometimes warning readers that the flow may be severely reduced during dry periods. Indeed, many visitors are disappointed when they see falls at such times. Some are saddened when the discharge of a waterfall has been depleted by the abstraction of water upstream for power generation or other purposes. While, for those in search of the Sublime or merely the superlative, size is often important, small waterfalls can give great pleasure to lovers of landscape beauty. According to guidebooks, however, even these falls are usually best seen after rain. Drawing on tourist and travel literature and personal journals from the eighteenth century to the present, and with reference to examples from different parts of the world, this paper discusses the importance of discharge in the tourist experience of waterfalls.

Employing the five-factor mentoring instrument : analysing mentoring practices for teaching primary science.

Primary science education is a concern around the world and quality mentoring within schools can develop preservice teachers’ practices. A five-factor model for mentoring has been identified, namely, personal attributes, system requirements, pedagogical knowledge, modelling, and feedback. Final-year preservice teachers (mentees, n=211) from three Turkish universities were administered a previously validated instrument to gather perceptions of their mentoring in primary science teaching. ANOVA indicated that each of these five factors was statistically significant (p<.001) with mean scale scores ranging from 3.36 to 4.12. Although mentees perceived their mentors to provide evaluation feedback (95%), model classroom management (88%), guide their preparation (96%), and outline the science curriculum (92%), the majority of mentors were perceived not to assist their mentees in 10 of the 34 survey items. Professional development programmes that target the specific needs of these mentors may further enhance mentoring practices for advancing primary science teaching.

Combination strategies for a factor analysis phone-conditioned speaker verification system

This work aims to take advantage of recent developments in joint factor analysis (JFA) in the context of a phonetically conditioned GMM speaker verification system. Previous work has shown performance advantages through phonetic conditioning, but this has not been shown to date with the JFA framework. Our focus is particularly on strategies for combining the phone-conditioned systems. We show that the classic fusion of the scores is suboptimal when using multiple GMM systems. We investigate several combination strategies in the model space, and demonstrate improvement over score-level combination as well as over a non-phonetic baseline system. This work was conducted during the 2008 CLSP Workshop at Johns Hopkins University.