The emergence of social networks and other interaction networks have brought to fore the questions of processing massive graphs. The (semi) streaming model, where we assume that the space is (near) linear in the number of vertices (but not necessarily the edges) is an useful and efficient model for processing large graphs. In many of these graphs the numbers of vertices are significantly less t...

In this paper, a Job shop scheduling problem with a parallel assembly stage and Lot Streaming (LS) is considered for the first time in both machining and assembly stages. Lot Streaming technique is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. Hence, to solve job shop scheduling problem with a parallel assembly stage and lot streaming, deci...

This paper addressed a Flexible Job shop Scheduling Problem (FJSP) with the objective of minimization of maximum completion time (Cmax) which job splitting or lot streaming is allowed. Lot streaming is an important technique that has been used widely to reduce completion time of a production system. Due to the complexity of the problem; exact optimization techniques such as branch and bound alg...

Previous research has established several methods of online learning for latent Dirichlet allocation (LDA). However, streaming learning for LDA— allowing only one pass over the data and constant storage complexity—is not as well explored. We use reservoir sampling to reduce the storage complexity of a previously-studied online algorithm, namely the particle filter, to constant. We then show tha...

The Paris terrorist attacks occurred on November 13, 2015 prompted a massive response on social media including Twitter, with millions of posted tweets in the first few hours after the attacks. Most of the tweets were condemning the attacks and showing support to Parisians. One of the trending debates related to the attacks concerned possible association between terrorism and Islam and Muslims ...

This paper describes an original strategy for using a datadriven probabilistic motion model into particle filter-based target tracking on video streams. Such a model is based on the local motion observed by the camera during a learning phase. Given that the initial, empirical distribution may be incomplete and noisy, we regularize it in a second phase. The hybrid discrete-continuous probabilist...

We present measurements of stream lifetimes for Internet traffic on a backbone link in California and a university link in Auckland. We investigate the consequences of sampling techniques such as ignoring streams with six or fewer packets, since they usually account for less than 10% of the total bytes. We find that we often observe large bursts of small ‘attack’ streams, which will diminish th...

For any p ∈ [0, 2], we give a 1-pass poly(ε−1 logn)-space algorithm which, given a data stream of length m with insertions and deletions of an n-dimensional vector a, with updates in the range {−M,−M +1, · · · ,M −1,M}, outputs a sample of [n] = {1, 2, · · · , n} for which for all i the probability that i is returned is (1 ± ) |ai| p Fp(a) ± n−C , where ai denotes the (possibly negative) value ...

Prior user studies in the music information retrieval field have identified different personas representing the needs, goals, and characteristics of specific user groups for a usercentered design of music services. However, these personas were derived from a qualitative study involving a small number of participants and their generalizability has not been tested. The objectives of this study ar...