38 research outputs found
Poshan Abhiyaan and MCH card awareness among pregnant and postpartum mothers, Raigad district, Maharashtra
No full textThe MCH card is increasingly recognized as an essential tool for maintaining maternal and child health within the expanded coverage of ICDS (Integrated Child Development System) and NRHM (Rural Health Mission). Nation).The POSHAN ABHIYAAN program also advocates for the widespread use of MCH cards and services. The study aims to assess the level of awareness about POSHAN ABHIYAAN and MCH (Maternal Child Health) card among the pregnant and post partum mothers. Method: The study was conducted from 22 February 2021 to 12 April 2021 among 80 pregnant and post partum mothers at the anganwadi centers of Maharashtra state selected by multistage sampling technique. Socio-demographic data along with components of POSHAN ABHIYAAN and MCH card were assessed. Data were collected, entered in MS Excel spreadsheet, and analyzed using SPSS software (version 20.0) Results: 85% were aware about the MCH card. Among them 73.8% carried the MCH card during the regular check-up. 78.8% were aware about 2 T.T. injection doses but only 66.3% were aware about the blood pressure monitored at regular check-up. 83.75% and 5% had average and good level of POSHAN ABHIYAAN awareness. POSHAN ABHIYAAN awareness need to be strengthened with involvement of family members
Poshan Abhiyaan and MCH card awareness among pregnant and postpartum mothers, Raigad district, Maharashtra
No full textThe MCH card is increasingly recognized as an essential tool for maintaining maternal and child health within the expanded coverage of ICDS (Integrated Child Development System) and NRHM (Rural Health Mission). Nation).The POSHAN ABHIYAAN program also advocates for the widespread use of MCH cards and services. The study aims to assess the level of awareness about POSHAN ABHIYAAN and MCH (Maternal Child Health) card among the pregnant and post partum mothers. Method: The study was conducted from 22 February 2021 to 12 April 2021 among 80 pregnant and post partum mothers at the anganwadi centers of Maharashtra state selected by multistage sampling technique. Socio-demographic data along with components of POSHAN ABHIYAAN and MCH card were assessed. Data were collected, entered in MS Excel spreadsheet, and analyzed using SPSS software (version 20.0) Results: 85% were aware about the MCH card. Among them 73.8% carried the MCH card during the regular check-up. 78.8% were aware about 2 T.T. injection doses but only 66.3% were aware about the blood pressure monitored at regular check-up. 83.75% and 5% had average and good level of POSHAN ABHIYAAN awareness. POSHAN ABHIYAAN awareness need to be strengthened with involvement of family members.</jats:p
An Artificial Neural Network Model For Estimating Paddy Crop Using Remotely Sensed Information For Davangere Region
No full textCrop yield forecasting is a very important task for researchers in remote sensing. Problems exist with traditional statistical modelling (especially regression models) of nonlinear functions with multiple factors in the cropland ecosystem. This paper describes the successful application of an artificial neural network in developing a model for crop yield forecasting using back-propagation algorithms. The model has been adapted and calibrated using on the ground survey and statistical data, and it has proven to be stable and highly accurate. This study presents a novel approach for predicting paddy yield using artificial neural networks (ANNs) and remote sensing data. The accurate estimation of crop yield is crucial for effective agricultural planning and resource allocation. In this research, remote sensing data, including satellite imagery and climate variables, were integrated into an ANN model to forecast paddy yield. The ANN model was trained and validated using historical yield data and corresponding remote sensed inputs.The results demonstrate the effectiveness of the proposed approach in accurately predicting paddy yield. The ANN model's ability to capture complex relationships between remote sensing variables and yield parameters is highlighted. The integration of remote sensing data provides valuable insights into the spatial and temporal dynamics of the crop growth process. This enables informed decision-making for farmers and policymakers. Furthermore, the study discusses the significance of accurate yield prediction in mitigating the impacts of climate variability and ensuring food security. The application of ANN-based yield estimation using remote sensed data holds promise for enhancing agricultural productivity and resource management. This research contributes to the growing field of precision agriculture by showcasing a data-driven approach that leverages advanced techniques to improve crop yield predictions.In conclusion, the utilization of artificial neural networks in conjunction with remote sensing data presents a robust method for predicting paddy yield. The findings underscore the potential benefits of integrating cutting-edge technology into agriculture, emphasizing the need for further research and practical implementation of such models on a broader scale
