Dow Chemical (South Korea)

Within a large integrated health care system that includes local, regional, and national medical centers and offices, quality and patient safety teams, and research institutes, more than 58 000 nurses are employed, with the vast majority providing point-of-care service to patients and members. A small but increasingly important number of nurses are involved in quality improvement and research teams to improve patient care. Within this environment, a number of developments point to a growing need for nursing leadership in systems-level and delivery science policies and research. This article describes a partnership between clinical operations leaders and researchers (nurse scientists) to determine and utilize evidence-based practices to meet a system goal. The first objective of this article is to describe the barriers and potential solutions in combining practice, quality improvement, and research efforts across regions within a large integrated health care system. The second objective is to describe the uniqueness and importance of nurse leaders across interdisciplinary teams to simultaneously pursue research, quality improvement, and operational goals for the organization.

The problem of distributing virtual machine (VM) images to a set of distributed compute nodes in a Cross-Cloud computing environment is considered as the main issue in this paper. Here the term Cross-Cloud Computing refers to the environment with multiple cloud sites. Self Scheduling schemes are mostly used for high performance as they represent adaptive schemes where allocation is done in run time. From review it is observed that Factorizing Self Scheduling (FSS) offers better load balance when execution time changes widely and randomly. Here, Heterogeneous Factorizing Self- Scheduling (HFSS) algorithm is proposed and considered for the implementation of virtual machine scheduling in crosscloud computing environment. Such an implementation is not yet done with cross-cloud platform which is proposed here. Another feature of the project is that, data sent by user for computation on cloud environment is stored in encrypted form. Data Encryption Standard (DES) is used for Integration of storage encryption & decryption.

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