The Experts below are selected from a list of 62295 Experts worldwide ranked by ideXlab platform

Daniel C. Sturman - One of the best experts on this subject based on the ideXlab platform.

  • DISC - Subscription propagation and content-based routing with delivery guarantees
    Lecture Notes in Computer Science, 2005
    Co-Authors: Yuanyuan Zhao, Sumeer Bhola, Daniel C. Sturman
    Abstract:

    Subscription propagation enables efficient content-based routing in publish/subscribe systems and is a challenging problem when it is required to support reliable delivery in networks with redundant routes. We have designed a Generic model and a highly-asynchronous Algorithm accomplishing these goals. Existing Algorithms can be interpreted as different encodings and optimizations of the Generic Algorithm and hence their correctness can be derived from the Generic Algorithm.

  • Brief Announcement:Subscription Propagation and Content-Based Routing with Delivery Guarantees
    2005
    Co-Authors: Yuanyuan Zhao, Sumeer Bhola, Daniel C. Sturman
    Abstract:

    Subscription propagation enables efficient content-based routing in publish/subscribe systems and is a challenging problem when it is required to support reliable delivery in networks with redundant routes. We have designed a Generic model and a highly-asynchronous Algorithm accomplishing these goals. Existing Algorithms can be inter- preted as different encodings and optimizations of the Generic Algorithm and hence their correctness can be derived from the Generic Algorithm.

Y. Shan - One of the best experts on this subject based on the ideXlab platform.

  • CSB Workshops - A Generic Algorithm to find all common intervals of two permutations
    2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05), 1
    Co-Authors: G. Feng, Y. Shan
    Abstract:

    Let K he the set of {1,2,....,m}, [x, y] denote the set of [x,x+1,...,y], where 1/spl les/x,y/spl les/m. Given two permutations /spl sigma//sub A/ and /spl sigma//sub B/ of a set /spl aleph/, A 2-tuple of intervals ([x/sub 1/, y/sub 1/], [x/sub 2/, y/sub 2/]) is called common intervals if /spl sigma//sub A/([x/sub 1/, y/sub 1/])=([x/sub 2/, y/sub 2/]). In this paper, we propose a sufficient and necessary condition for a 2-tuple of intervals to be common intervals. Based on these conditions, we present a Generic Algorithm that finds all common intervals of these two permutations.

Yuanyuan Zhao - One of the best experts on this subject based on the ideXlab platform.

  • DISC - Subscription propagation and content-based routing with delivery guarantees
    Lecture Notes in Computer Science, 2005
    Co-Authors: Yuanyuan Zhao, Sumeer Bhola, Daniel C. Sturman
    Abstract:

    Subscription propagation enables efficient content-based routing in publish/subscribe systems and is a challenging problem when it is required to support reliable delivery in networks with redundant routes. We have designed a Generic model and a highly-asynchronous Algorithm accomplishing these goals. Existing Algorithms can be interpreted as different encodings and optimizations of the Generic Algorithm and hence their correctness can be derived from the Generic Algorithm.

  • Brief Announcement:Subscription Propagation and Content-Based Routing with Delivery Guarantees
    2005
    Co-Authors: Yuanyuan Zhao, Sumeer Bhola, Daniel C. Sturman
    Abstract:

    Subscription propagation enables efficient content-based routing in publish/subscribe systems and is a challenging problem when it is required to support reliable delivery in networks with redundant routes. We have designed a Generic model and a highly-asynchronous Algorithm accomplishing these goals. Existing Algorithms can be inter- preted as different encodings and optimizations of the Generic Algorithm and hence their correctness can be derived from the Generic Algorithm.

Bernard F Fuemmeler - One of the best experts on this subject based on the ideXlab platform.

  • a Generic Algorithm for sleep wake cycle detection using unlabeled actigraphy data
    IEEE-EMBS International Conference on Biomedical and Health Informatics, 2019
    Co-Authors: Shanshan Chen, Robert A Perera, Matthew M Engelhard, Jessica R Lunsfordavery, Scott H Kollins, Bernard F Fuemmeler
    Abstract:

    One key component when analyzing actigraphy data for sleep studies is sleep-wake cycle detection. Most detection Algorithms rely on accurate sleep diary labels to generate supervised classifiers, with parameters optimized for a particular dataset. However, once the actigraphy trackers are deployed in the field, labels for training models and validating detection accuracy are often not available. In this paper, we propose a Generic, training-free Algorithm to detect sleep-wake cycles from minute-by-minute actigraphy. Leveraging a robust nonlinear parametric model, our proposed method refines the detection region by searching for a single change point within bounded regions defined by the parametric model. Challenged by the absence of ground truth labels, we also propose an evaluation metric dedicated to this problem. Tested on week-long actigraphy from 112 children, the results show that the proposed Algorithm improves on the baseline model consistently and significantly $(\mathbf{p} . Moreover, focusing on the commonality in human circadian rhythm captured by actigraphy, the proposed method is Generic to data collected by various actigraphy trackers, circumventing the laborious label collection step in developing customized classifiers for sleep detection.

  • a Generic Algorithm for sleep wake cycle detection using unlabeled actigraphy data
    arXiv: Applications, 2019
    Co-Authors: Shanshan Chen, Robert A Perera, Matthew M Engelhard, Jessica R Lunsfordavery, Scott H Kollins, Bernard F Fuemmeler
    Abstract:

    One key component when analyzing actigraphy data for sleep studies is sleep-wake cycle detection. Most detection Algorithms rely on accurate sleep diary labels to generate supervised classifiers, with parameters optimized for a particular dataset. However, once the actigraphy trackers are deployed in the field, labels for training models and validating detection accuracy are often not available. In this paper, we propose a Generic, training-free Algorithm to detect sleep-wake cycles from minute-by-minute actigraphy. Leveraging a robust nonlinear parametric model, our proposed method refines the detection region by searching for a single change point within bounded regions defined by the parametric model. Challenged by the absence of ground truth labels, we also propose an evaluation metric dedicated to this problem. Tested on week-long actigraphy from 112 children, the results show that the proposed Algorithm improves on the baseline model consistently and significantly (p<3e-15). Moreover, focusing on the commonality in human circadian rhythm captured by actigraphy, the proposed method is Generic to data collected by various actigraphy trackers, circumventing the laborious label collection step in developing customized classifiers for sleep detection.

Pontus Vikstål - One of the best experts on this subject based on the ideXlab platform.