Many state-of-the-art selectivity estimation methods use query feedback to maintain histogram buckets, thereby using the limited memory efficiently. However, they are ‘‘reactive’’ in nature, that is, they update the histogram based on queries that have come to the system in the past for evaluation. In some applications, future occurrences of certain queries may be predicted and a ‘‘proactive’’ ...

Accurate calibration of probabilistic predictive models learned is critical for many practical prediction and decision-making tasks. There are two main categories of methods for building calibrated classifiers. One approach is to develop methods for learning probabilistic models that are wellcalibrated, ab initio. The other approach is to use some post-processing methods for transforming the ou...

Normal mode analysis offers an efficient way of modeling the conformational flexibility of protein structures. We use anisotropic displacement parameters from crystallography to test the quality of prediction of both the magnitude and directionality of conformational flexibility. Normal modes from four simple elastic network model potentials and from the CHARMM force field are calculated for a ...

We present an improved, prescient, scheme to deliver pre-encoded video streams at very low latency. We dynamically manage the prediction dependency for a group of packets using a ratedistortion (R-D) optimization framework that adapts to the channel, so that the expected end-to-end distortion is minimized under a given rate constraint. In our system, the R-D characteristics of each prediction m...

We propose a histogram clustering (HC) method to accelerate fluorescence lifetime imaging (FLIM) analysis in pixel-wise and global fitting modes. The proposed method’s principle was demonstrated, the combinations of HC with traditional FLIM were explained. assessed methods both simulated experimental datasets. results reveal that not only increases speed (up 106 times) but also enhances estimat...

In this paper, based on two-dimensional difference histogram modification, a novel reversible data hiding (RDH)scheme is proposed by using binary space partition technique. The existing method data hiding is done by using difference pair-mapping and the data hiding aims to embed secret message into cover image. It is a natural extension of expansion embedding and shifting techniques used in cur...

BACKGROUND We review three common methods to estimate predicted probabilities following confounder-adjusted logistic regression: marginal standardization (predicted probabilities summed to a weighted average reflecting the confounder distribution in the target population); prediction at the modes (conditional predicted probabilities calculated by setting each confounder to its modal value); and...

The conductor corona noise of four local 400 kV AC transmission lines is measured and compared to predictions. The prediction software developed is based on the EPRI semi-analytical approach using excitation functions and the theory of natural modes. The nature and accuracy of the prediction software is discussed along with relevant corona noise metrology issues encountered.

During medical treatment, personal privacy is involved and must be protected. Healthcare institutions have to keep images or health information secret unless they permission from the data owner disclose them. Reversible hiding (RDH) a technique that embeds metadata into an image can recovered without any distortion after hidden been extracted. This work aims develop fully reversible two-bit emb...