Text sifting is a method of quickly and securely identifying documents for database searching, copy detection, duplicate email detection and plagiarism detection. A small amount of text is extracted from a document using hash functions and is used as the document’s fingerprint. We build upon previous work by Broder et al. [4,5] and Heintze [8], specifically addressing a certain set of attacks t...

Recent developments in analysis methods on the non-linear and non-stationary data have received large attention by the image analysts. In 1998, Huang introduced the empirical mode decomposition (EMD) in signal processing. The EMD approach, fully unsupervised, proved reliable monodimensional (seismic and biomedical) signals. The main contribution of our approach is to apply the EMD to texture ex...

Mobile Cloud Computing is process to compute the resources between multiple mobile devices. The mobile users demand a certain level of quality of services (QoS) of their device. If the mobile change the interface gateway in the mobility of device. In this paper we are Identify, Formulate, and address the problem of QoS. The process of Bandwidth sifting and redistribution by interfacing gateway ...

This work deals with the decomposition of a signal into a collection of intrinsic mode functions. More specifically, we aim to revisit Empirical Mode Decomposition (EMD) based on a sifting process step, which highly depends on the choice of an interpolation method, the number of inner iterations, and that does not have any convergence guarantees. The proposed alternative to the sifting process ...

We study a model sifting problem introduced by Selberg, in which all of the primes have roughly the same size. We show that the Selberg lower bound sieve is asymptotically optimal in this setting, and we use this to give a new lower bound on the sifting limit βκ in terms of the sifting dimension κ. We also show that one can use a rounding procedure to improve on the Selberg lower bound sieve by...

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent the Fast Fourier Transform (FFT). Both carry strong a-priori assumptions about the source data, such as linearity, of being stationary, and of satisfjmg the Dirichlet conditions. A recent development at the National Aeronautics an...