Performance-oriented Cloud Provisioning: Taxonomy and Survey

Cloud computing is being viewed as the technology of today and the future. Through this paradigm, the customers gain access to shared computing resources located in remote data centers that are hosted by cloud providers (CP). This technology allows for provisioning of various resources such as virtual machines (VM), physical machines, processors, memory, network, storage and software as per the needs of customers. Application providers (AP), who are customers of the CP, deploy applications on the cloud infrastructure and then these applications are used by the end-users. To meet the fluctuating application workload demands, dynamic provisioning is essential and this article provides a detailed literature survey of dynamic provisioning within cloud systems with focus on application performance. The well-known types of provisioning and the associated problems are clearly and pictorially explained and the provisioning terminology is clarified. A very detailed and general cloud provisioning classification is presented, which views provisioning from different perspectives, aiding in understanding the process inside-out. Cloud dynamic provisioning is explained by considering resources, stakeholders, techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table

Where to find facial artery perforators: a reference point

Reconstructive surgery of the midface using facial artery perforator (FAP) flaps is being used more frequently now as it has been reported to provide better aesthetic results and reduce a traditional two-stage procedure to a one-stage technique. Wide acceptance of this approach is limited by poor understanding of the anatomy associated with this technique however. This was investigated through a cadaveric study. The facial artery (FA) of 16 cadaveric half faces were each identified, cannulated with coloured latex, and then dissected to give an accurate and quantified description of FA perforating branches. A lateral view picture of each specimen was taken and analysed using ImageJ 1.42q. Cadaveric dissections showed that each hemiface could be regarded as a single entity. Means: FA length = 116±22 mm, FA diameter = 2.62±0.74mm, number of FAPs = 4±2, FAP length = 14.12±3.46 mm, FAP diameter = 0.94±0.29 mm. A reference point, A, where FAPs were consistently found to originate was also identified. Therefore, the FAP flap is a viable and valuable addition to plastic reconstructive techniques. The localisation of point A with precise measurements can facilitate the design and use of such FAP flaps for the reconstruction of nasal, as well as perinasal and perioral defects

Can Autism be Catered with Artificial Intelligence-Assisted Intervention Technology? A Literature Review

This article presents an extensive literature review of technology based intervention methodologies for individuals facing Autism Spectrum Disorder (ASD). Reviewed methodologies include: contemporary Computer Aided Systems (CAS), Computer Vision Assisted Technologies (CVAT) and Virtual Reality (VR) or Artificial Intelligence (AI)-Assisted interventions. The research over the past decade has provided enough demonstrations that individuals with ASD have a strong interest in technology based interventions, which are useful in both, clinical settings as well as at home and classrooms. Despite showing great promise, research in developing an advanced technology based intervention that is clinically quantitative for ASD is minimal. Moreover, the clinicians are generally not convinced about the potential of the technology based interventions due to non-empirical nature of published results. A major reason behind this lack of acceptability is that a vast majority of studies on distinct intervention methodologies do not follow any specific standard or research design. We conclude from our findings that there remains a gap between the research community of computer science, psychology and neuroscience to develop an AI assisted intervention technology for individuals suffering from ASD. Following the development of a standardized AI based intervention technology, a database needs to be developed, to devise effective AI algorithms