Data dissemination is an important application in vehicular networks. We observe that messages in vehicular networks are usually subject to both time and space constraints, and therefore should be disseminated during a specified duration and within a specific coverage. Since vehicles are moving in and out of a region, dissemination of a message should be repeated to achieve reliability. However...

The evaluation of summaries is a challenging but crucial task of the summarization field. In this work, we propose to learn an automatic scoring metric based on the human judgements available as part of classical summarization datasets like TAC-2008 and TAC-2009. Any existing automatic scoring metrics can be included as features, the model learns the combination exhibiting the best correlation ...

We consider an array error model for data in matrix form, where the corrupted symbols are confined to a number of lines (rows and columns) of the matrix. Codes in array metric (maximum term rank metric) are well suited for error correction in this case. We generalize the array metric to the case when the reliability of every line of the matrix is available. We propose a minimum distance decoder...

The emerging Internet of Things (IoT) connects the physical world to the digital one and composes large networks of smart devices to support various applications. In order to provide a suitable communication in such networks, a reliable routing protocol is needed. In this paper, a modified version of an IPv6 Routing Protocol for Low-Power and Lossy networks (RPL), which has been standardized by...

With the increase in deployment of multi-hop wireless networks and the desire for seamless internet access through ubiquitous connectivity, the inter-working of heterogeneous multi-hop wireless networks will become prominent in the near future. To complement the quest for ubiquitous service access, multi-mode mobile terminals are now in existence. Inter-working heterogeneous multi-hop wireless ...

Mahalanobis distance metric takes feature weights and correlation into account in the distance computation, which can improve the performance of many similarity/dissimilarity based methods, such as kNN. Most existing distance metric learning methods obtain metric based on the raw features and side information but neglect the reliability of them. Noises or disturbances on instances will make cha...

This article is a summary of a review journal article describing some of the recent research into the capacity value of wind power. With the worldwide increase in wind power during the past several years, there is increasing interest and significance regarding its capacity value. This has a direct influence on the amount of other (non-wind) capacity that is needed in future power systems. Recen...