Many organizations are now migrating to the cloud and investing in this technology. The cloud computing has solved many problems of the traditional computing, such as handling peak loads(storage), installing software updates, high availability of services and maintenance for cloud customers at  reasonable cost.

Due to the fact that the services and information of many organizations had been outsourced in the cloud, it becomes impossible to place a virtual protection and to create boundaries around the organization castle.

 The new technology has created new challenges such as data security.

The data security has always remained major issue in the IT, but in the cloud it becomes a serious concern since the data will be distributed at different places all over the globe and the resources are shared by different customers so it makes it difficult to clearly identify, authenticate, authorize and monitor who is accessing the customer’s data.

The appraisal of several performance measure agendas and metrics already accessible proposes that supply chain performance measure can be detected under different categories such as cost and non-cost; strategic and operational level; financial and business process perspective; customer, financial, internal operation, learning and growth perspective. Lack of appropriate knowledge in supply chain management that touches project success can lead to increased cost and delays. Hiring supply chain management in IT industry, with respect to their huge size and large investments, may help to elevate use of resources and implementation time. For this purpose, supply chain management may be used to evaluate chain performance, set future performance goals, and draw appropriate path for project success. This requires a comprehensive means and measures to assess different aspects of supply chain and make systematic evaluation possible. In this study, we have developed supply chain of IT industry based on BSC from existing decision making models. Then, industrial projects performance and performance evaluation measures have been determined using a designed questionnaire. Finally, project performance evaluation measures are proposed based on lean thinking principles and ranked using Expert Choice software.

Qualitative evaluation is one of the important approaches which has been utilized for the students of elementary level towards the fundamental ideal of the pedagogical system. The goal of this study has been to declare the differences between the qualitative evaluation and the students’ positive concept in the period of 1392 and 1393. The sample of the study has been recruited from 300 elementary students from sextuple regions of Esfahan, which has been chosen randomly according to the volume of the region. The method of the study has been quality. In this research, we have utilized the questionnaire created by the qualitative evaluation and standard self- concept questionnaire. The self- concept questionnaire is of construct validity and the researchers’ questionnaire is written by the qualitative evaluation which has been authorized by the education science experts and is consisted of content and formal validity. Their reliability for qualitative evaluation questionnaire with the Cronbach Alpha factor has been summed 0,876 as well as for self-concept questionnaire with the result of 0, 91. The accumulated results of this study has been analyzed by one sample T-test and Multiple Regression Test. The results of the statistical analysis showed that  the multiple relationship between  dimensions of  qualitative evaluation and the self -concept is (R= 0,72) and the Coefficient of Determination is (P= 0,000 and 0,52) and beta coefficient  respectively  for portfolio dimension is (P= 0,000 and β= 0,429), check list dimension is (β= 0,368 and P=0,000), record anecdotal is (P= 0,000 and β=0,331), self –assessment is (P=0,000 and β=0,317), performance Test is (P= 0,000 and β= 0,187), and achievement  Report is(β= 0,162 and P= 0,000).

In this paper, some modifications of Adomian decomposition method apply for solving nonlinear partial differential equations. These efficient modifications gives a simple powerful tool for obtaining the solutions without a need for large size of computations . The numerical results show the efficiency and accuracy of these methods.