In the era of deep learning, object detection plays an influential role for many industries. Detecting minute things are very much essential without human intervention especially at large scale industries. In this paper we have proposed multiple approaches for Multi-scale facial mask real time detection and classification for the hospital industry, crowd surveillance in the streets and malls are more useful in this COVID-19 Pandemic Situation. In our approach we have implemented two different detection models which are FMY3 using Yolov3 Algorithm and FMNMobile using NASNetMobile and Resnet_SSD300 Algorithms and used two different face mask dataset with 680 and 1400 images respectively. We have analyzed both the models by computing various probabilistic accuracy measures and achieved the 34% Mean Average Precision (mAP) and 91.7% Recall rate on FMY3 Model and achieved the 98% and 99% of accuracy and recall rate on FMNMobile Model. Finally we have shown results of various face mask detections from both the models.

Introduction: PROM is significant not only in perinatal morbidity and mortality, but also in the long-term neonatal complications and sequelae in survived neonates. The evaluation of neonatal sepsis is important so as to institute treatment as quickly as possible. Hence the present study is undertaken to determine the incidence of early onset neonatal sepsis in relation to PROM of more than 18 hours. Method: The present prospective study was conducted from December 2013 to November 2014 in GSL medical college and hospital, Rajahmundry. All the neonates born to mothers with history of prolonged rupture of membranes >18hrs during study period was formed sample size for present study. Institutional Ethical Clearance was obtained prior begin of the study. A detailed history was taken including age, parity, Obstetric history of the mother with emphasis on exact time of rupture of membranes, duration history and antibiotics before labour were evaluated. Result: The incidence of EONS in present study was found to be 14.5%. In present study the incidence of sepsis is higher in low birth weight neonates (66%) compared to normal birth weight babies (34%) and higher rate of incidence in preterm neonates (61.5%) than in term neonates (38.5%). Further, Staphylococcus aureus was the commonest isolate (45.45%) followed by CONS (27.27%). Conclusion: In conclusion, evaluation of neonatal sepsis is very important so as to institute treatment as quickly as possible.

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Background: Iron stores of neonates born to anaemic mothers are low, iron content in breast milk in anaemic women is low and because of these factors substantial proportion of infants become anaemic by six months. Thus maternal iron deficiency and anaemia makes the offspring vulnerable for developing iron deficiency anaemia right from infancy. The current study was made attempt to evaluate and establish the relationship between maternal haemoglobin and early neonatal outcome in term babies.Method: The present cross-sectional observational study conducted in term neonates and their mothers in first stage of labour in the Department of Paediatric and Department of Obstetrics & Gynaecology, GSL Medical College and general hospital, Rajamahendravaram, from 2015 to 2017. Relevant history of mother was recorded and blood sample from the mother was collected in first stage of labour for haemoglobin estimation.Result: The mean haemoglobin in anaemic mothers was found to be 9.48±0.413 gm/dl and that in non-anaemic mothers was 11.67±0.515gm/dl. Anaemia among mothers has significant effect on birth weight of the newborn babies, on crown heel length of the newborn babies (P<0.05) and on head circumference of Newborn babies (P< 0.05). It was found that anaemia among mothers has no significant effect on APGAR score at 5 mins and on hospital stay.Conclusion: Anaemic mothers had newborn with low mean birth weight, low mean head circumference and low crown heel length compared to the those of non anaemic mothers.