Drilling is a quite common operation being performed in the manufacturing of components. Instrumental response in drilling is geometrical accuracy and surface integrity of the drilled parts. For the application where geometrical tolerance is very small, an operation is to be carried out very carefully. If not, rejection of drilled samples will be higher and consequently production loss will be higher. The use of prediction model in this scenario is much more appropriate and cost-effective. This research aimed to apply extreme gradient boosting (XGBoost) regressor to develop a drilling prediction model. Drilling experiments were conducted after developing design of experiments with twenty-seven unique sets. Experimental data analysis was then carried out on experimental data sets that have features such as speed, feed, angle, hole length, and surface roughness. After correlation analysis, the k-fold cross validation method was applied for parameterisation. Hyperparameters estimated from the k-fold cross validation were then applied to train and test the XGBoost regressor-based machine learning (ML) model. It is concluded from the model evaluation metric (R2) that the XGBoost regressor model has resulted 0.89 before tuning and 0.94 after tuning of the model, which is higher than the polynomial regressor and support vector regressor.
<span lang="EN-US">Multilevel Inverters are generally utilized for medium voltage and high power applications. Invented in 1975, MLIs have brought huge change in the field of Electrical and Electronics. It contains distinctive topologies. This paper proposes a photovoltaic aided multilevel inverter with Reverse Voltage topology with diminished number of switches. In comparison to other existing topologies this topology utilizes minimum number of switches and less number of carrier signals which in turns diminishes the complexity of the system as well as cost. The proposed framework contains five MOSFETs, five diodes to create eleven levels. In this topology the SPWM strategy has been utilized. This topology utilizes one sine wave and five triangular waves, which is half in comparison to the existing topologies. As sustainable power sources can be utilized for multilevel inverter, photovoltaic cell has been utilized. The MATLAB recreation for both solar powered module and Multilevel inverter has been appeared alongside the equipment approach.</span>
Co 11015 (Atulya) has been notified for cultivation in Tamil Nadu as a short duration variety in the 83 rd meeting of Central Sub Committee on Crop Standards, Notification, Government of India. This variety combines high cane yield and high sucrose content right from 8 months to 12 months of crop age. Co 11015 is evolved from the cross CoC 671 and Co 86011 at ICAR-Sugarcane Breeding Institute, Coimbatore. The clone showed a remarkably good performance in the clonal trials with clear superiority over the standards Co 86032 and CoC 671. In station trials, it recorded a cane yield of 135.70 t ha -1 , sucrose of 21.46 % and sugar yield of 20.09 t ha -1 at 360 days. Fig. 2. Morphological features of sugarcane short duration variety Co 11015
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