A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerabl...A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent(xvariable) vs. daily rainfall(y-variable) provided the best fit to the data with a threshold equation of y = 80.7-0.1981 x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is~20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model(PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety(FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.展开更多
在基于Mesh-under的IPv6低功耗无线个域网(IPv6over low-power wireless personal area networks,6LoWPAN)中,针对传输路径上中间节点重传缓存溢出导致重传数据分片丢失,造成网络性能下降等问题,提出一种基于Mesh-under的备用缓存机制...在基于Mesh-under的IPv6低功耗无线个域网(IPv6over low-power wireless personal area networks,6LoWPAN)中,针对传输路径上中间节点重传缓存溢出导致重传数据分片丢失,造成网络性能下降等问题,提出一种基于Mesh-under的备用缓存机制。本文所提机制根据传输路径上各节点重传缓存使用情况及数据分片剩余跳数等信息,设置动态重传缓存门限,并为超过该门限的节点从其邻居节点中挑选合适的备用缓存节点,从而完成数据分片的缓存与重传过程,达到均衡使用各节点重传缓存的目的。结果表明,所提机制能够有效避免重传缓存溢出,减小网络能耗,同时进一步提高目的端重组成功率。展开更多
文摘A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent(xvariable) vs. daily rainfall(y-variable) provided the best fit to the data with a threshold equation of y = 80.7-0.1981 x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is~20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model(PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety(FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.
文摘在基于Mesh-under的IPv6低功耗无线个域网(IPv6over low-power wireless personal area networks,6LoWPAN)中,针对传输路径上中间节点重传缓存溢出导致重传数据分片丢失,造成网络性能下降等问题,提出一种基于Mesh-under的备用缓存机制。本文所提机制根据传输路径上各节点重传缓存使用情况及数据分片剩余跳数等信息,设置动态重传缓存门限,并为超过该门限的节点从其邻居节点中挑选合适的备用缓存节点,从而完成数据分片的缓存与重传过程,达到均衡使用各节点重传缓存的目的。结果表明,所提机制能够有效避免重传缓存溢出,减小网络能耗,同时进一步提高目的端重组成功率。