In this paper, seven self-accelerating iterative methods with memory are derived from an optimal two-step Steffensen-type method without memory for solving nonlinear equations, their orders of convergence are proved to be increased from 4 to 2 6 , (5 17) / 2 ,5 and (5 33) / 2 , numerical examples are demonstrat-ed demonstrated to verify the theoretical results, and applications for solving syst...

Using a probabilistic interpretation of an n dimensional extension of Papoulis's Generalized Sampling Theorem, an iterative algorithm has been devised for 3D reconstruction of a Lambertian surface at subpixel accuracy. The problem has been formulated as an optimization one in a Bayesian framework. The latter allows for introducing a priori information on the solution, using Markov Random Fields...

In view of the present cloud security problem has increasingly become one of the major obstacles hindering the development of the cloud computing, put forward a kind of memory based on Xen cloud environment security isolation technology implementation. And based on Xen virtual machine monitor system, analysis of the model of memory virtualization is implemented, using Xen memory virtualization ...

The higher resolution image can be reconstructed from lower resolution images using SuperResolution (SR) algorithm based on Support Vector Regression (SVR) by combining the pixel intensity values with local gradient information. Support Vector Machine (SVM) can construct a hyperplane in a high or infinite dimensional space which can be used for classification. Its regression version, Support Ve...

Multi agent system has been one of the most challenging parts in the field of artificial intelligence. Multiple agents are applied to do definite works using own intelligence. Communication is a medium through which agents can contact each other and perform at their best. In this paper we have formed multi agent communicative rule based architecture algorithmically. The framework depicts how th...

In this paper we discuss the use of self-organizing architectures for traffic management systems. We introduce Soteria, a multi-layered, integrated, super-infrastructure for traffic safety enhancement and congestion reduction. We highlight Soteria’s use of microand macro-level models and its hybrid top-down/bottom-up strategy for traffic management. We then present a generic architecture that c...

Super-resolution algorithms are facing a number of issues, in that image registration is one of the major challenges. Here, we need to generate an improved resolution image that is reconstructed based on several geometrically warped, linearly blurred and noisy images. The ultimate goal is to compute a high-resolution image from low resolution image. For this an approach which makes use of geome...

Future projection of climate is typically obtained by combining outputs from multiple Earth System Models (ESMs) for several climate variables such as temperature and precipitation. While IPCC has traditionally used a simple model output average, recent work has illustrated potential advantages of using a multitask learning (MTL) framework for projections of individual climate variables. In thi...

In this paper, we present the use of semantic caching in the environment of schema-based super-peer networks. Different from traditional caching, semantic caching allows the answering of queries that are not in the cache directly. The challenge of answering the queries using the cache is reduced to the problem of answering queries using materialized views. For this purpose, we implemented the M...

Learning based image super-resolution method is used to reconstruct high-frequency (HF) details from the prior model trained by a set of high-(HR) and low-resolution (LR) image patches. In this paper, newly proposed novel image superresolution method via dual-dictionary learning and sparse representation, which consists of the main dictionary learning and the residual dictionary learning, to re...