Today, context-aware systems are discussed as one of the key subjects in ubiquitous computing systems. In this area, researchers have been trying to find some techniques for context information modeling. So that attaining general and efficient model for managing, storing and retrieving data and contextual information becomes possible. In this regard and in order to achieving this goal, several methods have been proposed in literature. In our research and in this paper, object-based models and ontology-based models are introduced as two most famous models for modeling the context information along with some novel approaches that are based on The two mentioned models Our study introduces the key requirements of effective context-aware model and goes further to benchmark the models in question against those set of requirements.

In today’s world, complex global business environment is in a state of continuous change. Therefore, business organizations are looking for an innovative way to optimize and to support the performance of their business processes to meet out their market share in order to maintain a competitive edge. Usually, business processes are monitored in near real-time using Key Performance Indicators (KPI). KPI is in turn calculated from metrics from business processes. In the case of business outsourcing, the KPI calculation from the metrics of business process is to be carried out cutting across the inter-organizations boundaries and spanning multiple domains. This process poses several challenges in the computation of the KPIs. Some of these challenges include uncertainty in metric values, just-in-time KPI computation and scalability. To address the above challenges of business organizations, a four-tier Complex business Activity Monitoring system with Event Processing (CAMEP) is proposed. The performance evaluation of the proposed system is performed to demonstrate the effectiveness of the proposed CAMEP method by comparing with the existing BAM approaches. The proposed CAMEP is also analyzed using the ANOVA and T test.

The paper carefully analyses the impact of information technology on business process re-engineering with respect to organizational perspectives. This study recommends an outline for simplifying business process reengineering efforts in the direction of competitive firms. The framework was examined using sample data from the respondents who are all senior officers. The review outcomes specify that managerial innovation, market force and competitive force positively affect information technology implementation, which in turn elicit variations or business process in terms of workroom, labor force and commercial structure. The work formulates hypothesis for the factors that affect implementation of information technology in an organization and thereby proposes a model for implications of results.

Mutual funds are moving rapidly towards financial market development in response to huge market demand in Iran.so what is needed is a useful and applicable method for appraising and selecting them. Performance evaluation is one the most important point in investment .therefore, in this research we tried to compute and compare the performance of mutual funds by different models and compare them to market. So we have chosen 14 active mutual funds during the year 2008 to 2012 and calculate the risks and returns of these mutual funds, then we analyzed hypotheses. Results show that performance evaluation of modern and postmodern theory gives different ranking. At this period some mutual funds showed better performance than market and some on the contrary .Also results show that postmodern portfolio criteria were more successful for predicting return than modern criteria. At the end results of research recommend the use of postmodern criteria which are based on downside risk.

In this paper, we solve the integro-differential equation by using new integral transform called Tarig transform. New theorems for the transform of integrals are introduced and proved.

The denoising procedure attenuates the image noise while preserving its edges and fine details. In computed tomography, images are degraded by additive white Gaussian noise because of different acquisition and systems errors. Due to noise existence, specialists may encounter certain difficulties to analyze or extract the useful information from noisy images. This paper presents a novel implementation of the phase preserving algorithm to denoise CT images. The phase preserving is a very powerful noise reduction algorithm but it tends to remove specific small details from the processed CT images supposing these details as noise. Therefore, the Wiener filter is used along with the latter algorithm to reduce the noise and aids in conserving the minor medical details. Moreover, selected adjustments to the phase preserving algorithm are applied to obtain a better image contrast and quality. The performance of the proposed scheme is assessed on naturally and synthetically degraded CT images using the universal image quality index (UIQI) metric. Results show major improvement not only in noise attenuation but also in preserving the small details.