Augmented reality, the new age technology, has widespread applications in every field imaginable. This technology has proven to be an inflection point in numerous verticals, improving lives and improving performance. In this paper, we explore the various possible applications of Augmented Reality (AR) in the field of Medicine. The objective of using AR in medicine or generally in any field is the fact that, AR helps in motivating the user, making sessions interactive and assist in faster learning. In this paper, we discuss about the applicability of AR in the field of medical diagnosis. Augmented reality technology reinforces remote collaboration, allowing doctors to diagnose patients from a different locality. Additionally, we believe that a much more pronounced effect can be achieved by bringing together the cutting edge technology of AR and the lifesaving field of Medical sciences. AR is a mechanism that could be applied in the learning process too. Similarly, virtual reality could be used in the field where more of practical experience is needed such as driving, sports, neonatal care training.
This paper presents methodologies that provide better correlation between the apriori and posteriori estimation of interconnect length, width, area and power. A method to generate random realistic benchmark circuits for analysis is implemented. A prediction model that predicts the length, width, area and power of the benchmark circuit is developed. The net list is passed through the placement and routing phases to obtain the actual length. From the estimated length, the width, area and power are estimated. The effectiveness of the prediction technique used is validated from the results obtained. We postulate that the predicted area which comes out with a smaller error percentage than predicted length can be used as a termination condition in Simulated Annealing for placement. Results are compared for proving optimization with Lagrange's Method.
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