An advanced interest point detector is proposed to improve the Hessian-Matrix based detector of the SURF algorithm. Round-like shapes are utilized as the filter shape to calculate of the Hessian determinant. Dxy can be acquired from approximate round areas, while the regions for computing Dyy or Dxx are designed with the consideration to symmetry and a balance of pixel number. Experimental results indicate that the proposed method has higher repeatability than the one used in SURF, especially in the aspects of rotation and viewpoint, due to the centrosymmetry of the proposed filter shapes. The results of image matching also show that more precision can be gained with the application of proposed detector.

In this paper, we propose an anonymous routing protocol, LOPP, to protect the originator's location privacy in Delay/Disruption Tolerant Network (DTN). The goals of our study are to minimize the originator's probability of being localized (Pl) and maximize the destination's probability of receiving the message (Pr). The idea of LOPP is to divide a sensitive message into k segments and send each of them to n different neighbors. Although message fragmentation could reduce the destination's probability to receive a complete message, LOPP can decrease the originator's Pl. We validate LOPP on a real-world human mobility dataset. The simulation results show that LOPP can decrease the originator's Pl by over 54% with only 5.7% decrease in destination's Pr. We address the physical localization issue of DTN, which was not studied in the literature.

An important factor determining the performance of delay tolerant networks (DTNs) is packet delivery delay. In this paper, we study the block delivery delay of DTN with the epidemic routing scheme based on random linear network coding (RLNC). First, simulations show that the influence of relay buffer size on the delivery delay is not as strong in RLNC-based routing as it is in replica-based routing. With this observation,we can simplify the performance analysis by constraining the buffer of the relay node to just one size. Then we derive the cumulative distribution function (CDF) of block delivery delay with difference equations. Finally, we validate the correctness of our analytical results by simulations.

One of the main research tasks in community question answering (cQA) is finding the most relevant questions for a given new query, thereby providing useful knowledge for users. The straightforward approach is to capitalize on textual features, or a bag-of-words (BoW) representation, to conduct the matching process between queries and questions. However, these approaches have a lexical gap issue which means that, if lexicon matching fails, they cannot model the semantic meaning. In addition, latent semantic models, like latent semantic analysis (LSA), attempt to map queries to its corresponding semantically similar questions through a lower dimension representation. But alas, LSA is a shallow and linear model that cannot model highly non-linear correlations in cQA. Moreover, both BoW and semantic oriented solutions utilize a single dictionary to represent the query, question, and answer in the same feature space. However, the correlations between them, as we observe from data, imply that they lie in entirely different feature spaces. In light of these observations, this paper proposes a tri-modal deep belief network (tri-DBN) to extract a unified representation for the query, question, and answer, with the hypothesis that they locate in three different feature spaces. Besides, we compare the unified representation extracted by our model with other representations using the Yahoo! Answers queries on the dataset. Finally, Experimental results reveal that the proposed model captures semantic meaning both within and between queries, questions, and answers. In addition, the results also suggest that the joint representation extracted via the proposed method can improve the performance of cQA archives searching.

We analyze the defects of window-based TCP algorithm in datacenter networks and propose Rate-based Datacenter TCP (RDT) algorithm in this paper. The RDT algorithm combines rate-based congestion control technology with ECN (Explicit Congestion Notification) mechanism of DCTCP. The experiments in NS2 show that RDT has a potential to completely avoid TCP incast collapse in datacenters and inherit the low latency advantages of DCTCP.