Security within the cloud is of paramount importance as the interest and indeed utilization of cloud computing increase. Multitenancy in particular introduces unique security risks to cloud computing as a result of more than one tenant utilizing the same physical computer hardwareand sharing the same software and data. The purpose of this paper is to explore the specific risks in cloud computing due to Multitenancy and the measures that can be taken to mitigate those risks.

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Abstract-It is of little surprise that falling is often accepted as a natural part of the aging process. In fact, it is the impact rather than the occurrence of falls in the elderly, which is of most concern. Aging people are typically frailer, more unsteady, and have slower reactions, thus are more likely to fall and be injured than younger individuals. Typically, research and industry presented various practical solutions for assisting the elderly and their caregivers against falls via detecting falls and triggering notification alarms calling for help as soon as falls occur in order to diminish fall consequences.

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In the context of distance education, lab and field work are a considerable challenge for students, professors, and institutions. This paper presents a Telepresence Robot Empowered Smart Lab (TRESL) system as a new and emerging technology with a potential to overcome this challenge. The main focus of this paper is to propose a conceptual model, to define the ultimate goals of the proposed solution, and to present its system architecture and the modules to support the functions and features. A pilot project was conducted and is also presented in this paper. The pilot project includes the experimental implementation of a telepresence robot in a mock-up smart lab and the collection and analysis of survey data from users of the robot. The main findings of the pilot study are, 1) online users can easily operate the telepresence robot; and 2) operating the robot manually will increase the engagement of online users with the remote lab environment. The pilot study provides firm evidence that the proposed TRESL system is a promising and innovative approach for online students to conduct their lab work in a remote laboratory. The results also suggest avenues for further research and development of the system.

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Semi-supervised clustering is often viewed as using labeled data to aid the clustering process. However, existing algorithms fail to consider dual constraints between data points (e.g. documents) and features (e.g. words). To address this problem, in this paper, we propose a novel semi-supervised document co-clustering model OSS-NMF via orthogonal nonnegative matrix tri-factorization. Our model incorporates prior knowledge both on document and word side to aid the new wordcategory and document-cluster matrices construction. Besides, we prove the correctness and convergence of our model to demonstrate its mathematical rigorous. Our experimental evaluations show that the proposed document clustering model presents remarkable performance improvements with certain constraints.