Guest Editors' introduction: Special section on mining large uncertain and probabilistic databases

published_or_final_versio

A Self-Adaptive Regression-Based Multivariate Data Compression Scheme with Error Bound in Wireless Sensor Networks

Wireless sensor networks (WSNs) have limited energy and transmission capacity, so data compression techniques have extensive applications. A sensor node with multiple sensing units is called a multimodal or multivariate node. For multivariate stream on a sensor node, some data streams are elected as the base functions according to the correlation coefficient matrix, and the other streams from the same node can be expressed in relation to one of these base functions using linear regression. By designing an incremental algorithm for computing regression coefficients, a multivariate data compression scheme based on self-adaptive regression with infinite norm error bound for WSNs is proposed. According to error bounds and compression incomes, the self-adaption means that the proposed algorithms make decisions automatically to transmit raw data or regression coefficients, and to select the number of data involved in regression. The algorithms in the scheme can simultaneously explore the temporal and multivariate correlations among the sensory data. Theoretically and experimentally, it is concluded that the proposed algorithms can effectively exploit the correlations on the same sensor node and achieve significant reduction in data transmission. Furthermore, the algorithms perform consistently well even when multivariate stream data correlations are less obvious or non-stationary. </jats:p

Public Health for the Internet φ Towards A New Grand Challenge for Information Management

Business incentives have brought us within a small factor of achieving the database community\u27s Grand Challenge set out in the Asilomar Report of 1998. This paper makes the case for a new, focused Grand Challenge: Public Health for the Internet. The goal of PHI (or φ) is to enable collectives of hosts on the Internet to jointly monitor and promote network health by sharing information on network conditions in a peer-to-peer fashion. We argue that this will be a positive effort for the research community for a variety of reasons, both in terms of its technical reach and its societal impact. This version of the φ vision is targeted at readers in the database research community, but the effort is clearly multidisciplinary. A more generalist version of this paper will be maintained at http://openphi.net

Sucrose Monoester Micelles Size Determined by Fluorescence Correlation Spectroscopy (FCS)

One of the several uses of sucrose detergents, as well as other micelle forming detergents, is the solubilization of different membrane proteins. Accurate knowledge of the micelle properties, including size and shape, are needed to optimize the surfactant conditions for protein purification and membrane characterization. We synthesized sucrose esters having different numbers of methylene subunits on the substituent to correlate the number of methylene groups with the size of the corresponding micelles. We used Fluorescence Correlation Spectroscopy (FCS) and two photon excitation to determine the translational D of the micelles and calculate their corresponding hydrodynamic radius, Rh. As a fluorescent probe we used LAURDAN (6-dodecanoyl-2-dimethylaminonaphthalene), a dye highly fluorescent when integrated in the micelle and non-fluorescent in aqueous media. We found a linear correlation between the size of the tail and the hydrodynamic radius of the micelle for the series of detergents measured