Waning Immunity is an important and relevant concept during these days as the COVID-19 pandemic is expected to become endemic in the coming months. By definition, Waning Immunity is the loss of protective antibodies over time and hence necessitates booster shots at regular intervals of time. This quantitative study is on proposition of a model for computing a newly defined metric called Waning Immunity Index (WII). The model takes into account the three group of people namely, susceptible, infected and recovered individuals from the COVID-19 infections. The required data can be collected from the Kaggle repository that contains information on infections, recovery, vaccination and booster doses given on the human population while considering a geographical location. The proposed model and its implementation have thrown light on the spread, control and effect of COVID-19 virus. Results of the proposed model and the measurement can help health officials to seamlessly plan the duration of booster doses administered on vaccinated population. A sample data has been prepared for testing the model and the application of the proposed metrics. Based on the results, it is found that vulnerability of the Waning Immunity increases steeply at some duration and gradually steadies in time.
Cost effective, secure and environment friendly data centers are crucial for the success of embracing the adoption of Internet of Things (IoT). Regardless of the potential benefits of IoT, there are still many hurdles to be overcome to leverage the wide growth of the IoT technology.
One challenging vector is the efficient power profiling of the entities involved in an IoT ecosystem. Software-Defined Data Center (SDDC) virtualizes the key data center infrastructure such as compute, storage and network. IoT fabric with SDDC, due to virtualization and the reduction in the
hardware footprint, an extent of reduced power consumption is achieved when compared to a non-virtualized traditional data center. Today, in the end-to-end IoT and IT fabric, deficiency of intelligent power profiling techniques merits the need to supervise power in such an ecosystem, especially
from an OT/IT convergence point of view where SDDC represents IT (Information Technology) and IoT forms OT (Operational Technology). To that end, this paper looks at power profiling for IoT fabric with SDDC by modeling the IoT ecosystem using semantic approaches. Thus, we bring in a notion
of power awareness to the software defined IoT fabric. Specifically, this paper models a power profile ontology for the IoT fabric with SDDC and monitor such an ecosystem at run time and derive useful value by bridging the OT/IT convergence gap with respect to end-to-end power profiling.
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