A Bio-Wicking System to Mitigate Capillary Water in Base Course

Water within pavement layers is the major cause of pavement deteriorations. High water content results in significant reduction in soil’s resilient behavior and increase in permanent deformation. Conventional drainage systems can only drain gravity water but not capillary water. Both preliminary lab and field tests have proven the drainage efficiency of a newly developed H2Ri geotextile with wicking fabrics. This bio-wicking system aims at resolving the potential issues that the original design may encounter: (1) H2Ri ultraviolet degradation, (2) H2Ri mechanical failure, (3) loss of drainage function under high suction, and (4) clogging and salt concentration. Both elemental level and full-scale test results indicated that the bio-wicking system is more effective in draining capillary water within the base courses compared with original design, in which the geotextile is directly exposed to the open air. However, a good drainage condition is required for the bio-wicking system to maintain its drainage efficiency. Accumulation of excess water will result in water re-entering the road embankment. Moreover, grass root and geotextile share the same working mechanism in transporting water. In the proposed bio-wicking system, the relatively smaller channels in the grass roots further ensures water moving from H2Ri geotextile, transporting through the stems of grass, and eventually evapo-transpiring into the air at the leaf-air interfaces. In sum, the bio-wicking system seemed to successfully address the concerns in the preliminary design and is a more efficient system to dehydrate the road embankment under unsaturated conditions.TenCate Geosynthetic

Tracking Angles of Departure and Arrival in a Mobile Millimeter Wave Channel

Millimeter wave provides a very promising approach for meeting the ever-growing traffic demand in next generation wireless networks. To utilize this band, it is crucial to obtain the channel state information in order to perform beamforming and combining to compensate for severe path loss. In contrast to lower frequencies, a typical millimeter wave channel consists of a few dominant paths. Thus it is generally sufficient to estimate the path gains, angles of departure (AoDs), and angles of arrival (AoAs) of those paths. Proposed in this paper is a dual timescale model to characterize abrupt channel changes (e.g., blockage) and slow variations of AoDs and AoAs. This work focuses on tracking the slow variations and detecting abrupt changes. A Kalman filter based tracking algorithm and an abrupt change detection method are proposed. The tracking algorithm is compared with the adaptive algorithm due to Alkhateeb, Ayach, Leus and Heath (2014) in the case with single radio frequency chain. Simulation results show that to achieve the same tracking performance, the proposed algorithm requires much lower signal-to-noise-ratio (SNR) and much fewer pilots than the other algorithm. Moreover, the change detection method can always detect abrupt changes with moderate number of pilots and SNR.Comment: 6 pages, 7 figures, submitted to ICC 201

Solving the Cold-Start Problem in Recommender Systems with Social Tags

In this paper, based on the user-tag-object tripartite graphs, we propose a recommendation algorithm, which considers social tags as an important role for information retrieval. Besides its low cost of computational time, the experiment results of two real-world data sets, \emph{Del.icio.us} and \emph{MovieLens}, show it can enhance the algorithmic accuracy and diversity. Especially, it can obtain more personalized recommendation results when users have diverse topics of tags. In addition, the numerical results on the dependence of algorithmic accuracy indicates that the proposed algorithm is particularly effective for small degree objects, which reminds us of the well-known \emph{cold-start} problem in recommender systems. Further empirical study shows that the proposed algorithm can significantly solve this problem in social tagging systems with heterogeneous object degree distributions