—Over low bit rate channels, we adopt the streaming of nonlinearly sampled video frames (i.e., key-frame slideshow) synchronized with the audio stream. Given the channel and buffer limits, we wish to obtain a set of sampled frames that is not only feasible (i.e., no frame drop) but also optimal in terms of maximal information flow (given that the semantic information contents of each frame can ...

although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. this paper deals with scheduling jobs in lot streaming flexible flow line problems. the paper mathematically formulates the problem by a mixed integer linear programming model. this model solves small instances to optimality. moreo...

Social networks are streaming, diverse and include a wide range of edges so that continuously evolves over time and formed by the activities among users (such as tweets, emails, etc.), where each activity among its users, adds an edge to the network graph. Despite their popularities, the dynamicity and large size of most social networks make it difficult or impossible to study the entire networ...

We present a novel lossy compression algorithm for G-buffers that enables deferred shading applications with high visibility sampling rates. Our streaming compression method operates in a single geometry rendering pass with a fixed, but scalable, amount of per pixel memory. We demonstrate reduced memory requirements and improved performance, with minimal impact on image quality.

In this paper, we present a new algorithm for estimating the size of equality join of multiple database tables. The proposed algorithm, Correlated Sampling, constructs a small space synopsis for each table, which can then be used to provide a quick estimate of the join size of this table with other tables subject to dynamically specified predicate filter conditions, possibly specified over mult...

Bipartite graph data increasingly occurs as a stream of edges that represent transactions, e.g., purchases by retail customers. Applications such as recommender systems employ neighborhood-based measures of node similarity, such as the pairwise number of common neighbors (CN) and related metrics. While the number of node pairs that share neighbors is potentially enormous, in real-word graphs on...

Increasingly, organizations have employed methods to understand unstructured text across the web. Entity resolution is used to identify mentions in large, streaming text corpora. Sampling-based entity resolution using Markov Chain Monte Carlo (MCMC) techniques guarantees convergence to a stationary distribution and can jump out of a local optimum. When performing entity resolution over streams ...

In this paper we study how to perform distinct sampling in the streaming model where data contain near-duplicates. The goal of distinct sampling is to return a distinct element uniformly at random from the universe of elements, given that all the near-duplicates are treated as the same element. We also extend the result to the sliding window cases in which we are only interested in the most rec...

The analysis of data streams has become quite important in recent years, and is being studied intensively in fields such as database management and data mining. However, to date few researchers in data and information visualization have investigated the visual analytics of streaming data. Although streaming data is similar to time-series data, its large-scale and unbounded characteristics make ...