Novel ROADM modelling with WSS and OBS to Improve Routing Performance in Optical Network

The area of optical network is on constant point of focus among the research communities owing to potential advantage of long distance communication as well as the routing issues associated with it. Majority of the implemented techniques calls for using expensive hardware or adopting narrowed technical assumptions, for which reason the routing performance couldn’t be optimized to a large extent. The present manuscript proposes a novel technique called as Optimized Routing for Peak Traffic under the scenario of uncertainties in the existing traffic scenario. The proposed solution presents some potential principle that is incorporated in the ROADM design for enhancing the capabilities of the proposed system.  The system is evaluated under multiple scenarios of analysis using blocking probabilities, OSNR, bit error rate, iteration etc. The outcome of the proposed system is compared with the one of the existing significant study to benchmark it

A Study on C.5 Decision Tree Classification Algorithm for Risk Predictions During Pregnancy

AbstractComplication during pregnancy has turned out o be a major problem for women of today's era. Pregnant women must be protected from these complications arising in period of gestation, a stage wherein every woman undergoes many physiological changes, sometimes inducing severe health problems leading to death of both mother and fetus. Technological interventions in the field of medical diagnosis can largely help to find a solution for this problem to protecting pregnant women, thus in turn reducing maternal and fetal mortalities to great extents. Decision Tree Classification method is a popularly used method whose algorithms are best suitable in medical diagnosis. C4.5 Decision Tree algorithm is one of the popular and effectively used classifier for pregnancy data classification in present study. The main aim of this paper is to pinpoint the importance of standardization of parameters selected for data collection in study, compare the results obtained from C4.5 classifier on both un-standardized and standardized datasets and analyse the performance of the C4.5 algorithm in terms of its prediction accuracy when applied on the created database from collected and standardized pregnancy data