Increased use of autonomy also increases the need for humans to interact with or manage autonomy. We propose a new variation of sliding autonomy useful for planning problems over a spatial region. With this approach, the user can influence the behavior of the autonomous system via spatial constraints and temporal constraints. We present a set of user interface designs to implement sliding auton...

Although traditional databases and data warehouses have been exploited widely to manage persistent data, a large number of applications from sensor network need functional supports for transient data in the continuous data stream. One of the crucial functions is to summarize the data items within a sliding window. A sliding window contains a fixed width span of data elements. The data items are...

We have used the unique properties of macrocilia from the lips of the ctenophore Beroë to test whether the ciliary beat cycle is caused by sequential activation of doublet sliding on opposite sides of the axoneme (Satir, P., 1982, Soc. Exp. Biol. Symp., 35: 179-201; Sugino, K., and Y. Naitoh, 1982, Nature (Lond.), 295: 609-611; Wais-Steider, J., and P. Satir, 1979, J. Supramol. Struct., 11:339-...

Clustering queries over sliding windows require maintaining cluster memberships that change as windows slide. To address this, the Generic 2-phase Continuous Summarization framework (G2CS) utilizes a generation based window maintenance approach where windows are maintained over different time intervals. It provides algorithm independent and efficient sliding mechanisms for clustering queries wh...

Sliding-window aggregation is a widely-used approach for extracting insights from the most recent portion of a data stream. Most aggregation operations of interest can be cast as binary operators that are associative, but not necessarily commutative nor invertible. However, non-invertible operators are nontrivial to support efficiently. The best existing algorithms for this setting require Oplo...

In order to improve the prediction accuracy of chaotic time series, a chaotic time series forecasting method based on online weighted least squares support vector machine regression (WLS-SVM) is proposed. In this method, a sliding time window is built and data in the sliding time window are employed to construct the dynamic model of a system. The model of the system is refreshed on-line with th...

In order to incorporate the skyline operator into the data stream engine, we need to address the problem of skyline cardinality estimation, which is very important for extending the query optimizer’s cost model to accommodate skyline queries. In this paper, we propose robust approaches for estimating the skyline cardinality over sliding windows in the stream environment. We first design an appr...

Protein-protein interactions based on linear motif (LM) recognition play roles in many cell regulatory processes. The E. coli sliding clamp is a protein mediator of replisome formation, which uses a common surface pocket composed of two subsites (I and II) to interact with LMs in multiple binding partners. A structural and thermodynamic dissection of sliding clamp-LM recognition has been perfor...

We developed a software tool (SlidingBayes) for recombination analysis based on Bayesian phylogenetic inference. Sliding-Bayes provides a powerful approach for detecting potential recombination, especially between highly divergent sequences and complex HIV-1 recombinants for which simpler methods like neighbor joining (NJ) may be less powerful. SlidingBayes guides Markov Chain Monte Carlo (MCMC...