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Within medical imaging, there are various modalities of medical images like CT, X-rays, MRI and other modalities that provide information about a human body in different ways. Each modality has distinctive characteristics that provide various sources of information. Therefore, there are some problems like image comparison such as CT/PET, CT /MRI, and MRI/ PET were usually meet by the clinical treatment and diagnosis. Hence the need to combine the different images' information and this process is known as ‘medical image fusion’. In this paper, two techniques for the ‘medical image fusion’ are introduced. The first proposed fusion technique is the combination of the fast filtering with the discrete wavelet transform ‘DWT’ methods for overcoming the low spatial resolution fused image provided by DWT and preserve the source images' salient features. Where we used the fast filtering method procedures for combining the corresponding ‘low-frequency coefficients’ to maintain the ‘salient features’ of the initial images, and the maximum rule with the high-frequency coefficients which lead getting better the resultant image contrast. The second proposed technique is the combination of fast filtering with stationary wavelet transform (SWT) methods, where ‘SWT’ has the shift-invariant property which enables to overcome the shift-variance DWT's drawback. The performance of the fused output is tested and compared with five of the common fusion methods like the Gradient pyramid, Contrast pyramid, DWT, Fast Filtering, and SWT techniques, using performance parameters: E, SNR, SD, and PSNR.

Cloud Computing is, by nature, multi-tenant, complex, large-scale, and heterogeneous distributed systems. Thus respectively, its processes and strategies need to be automated and integrated. one of the essential processes in the Cloud computing system is negotiating the service level agreement which always has to be elastic and flexible in handling and translating the user services’ requirements. This paper aims at presenting an automated SLA negotiation framework based on autonomous and flexible agents and multi agent systems based on the autonomic computing features as suitable tools for self-detection of failures and self-monitoring for the Cloud operations and services.

To increase our understanding of the interactions between the different cellular and intercellular processes, it is imperative to construct accurate biological models. An important class of these models are usually used to predict the time evolution of the corresponding chemical species over a specified period of time. Stochastic and coloured stochastic Petri nets can be adopted to construct graphical models that can be executed to simulate the firing of a set of reactions in a well-mixed chemical system. For the purpose of this specific application, (coloured) stochastic Petri nets employ internally the stochastic simulation algorithm (SSA) to perform the simulation. Although the result of the SSA is accurate in comparison with similar numerical simulation approaches (e.g., the systems of ordinary differential equations), it is empirically considered as a computationally expensive algorithm. In this paper, we propose an efficient parallel simulation algorithm for SSA to improve the execution of (coloured) stochastic Petri nets. We illustrate our proposal by applying it to a well-known model in the biological context: reaction diffusion. Furthermore, we evaluate the performance of the parallel algorithm and compare its runtime behaviour with the sequential one.

The rapid spread of using Cloud services has become a source of attraction for many business owners due to its multiple potential benefits of flexibility and efficiency with variant pricing plans that can be suited for all types of users. However, there are some vulnerabilities that have important and influential impact on the Cloud Computing efficiency, specially its ability to achieve availability and security for its customers. In this paper we try to find a way for assessing some of public Cloud frameworks for the E-learning application from two points of view; the availability degree of the Cloud framework in both service's speed and cost, and the vulnerabilities and threats that may infect these frameworks. The paper also presents a developed risk assessment equation in attempting to measure the risk factor for each Cloud platform by measuring the impact of the probable threats on the existing vulnerabilities in every platform. The risk rate measurement may help the user in selecting the most proper framework to deploy his application.