Browsing by Author "A, Raksha"

COVID-19 is a worldwide epidemic, as announced by the World Health Organization (WHO) in March 2020. Machine learning (ML) and Digital Image Processing methods can play vital roles in identifying COVID-19 patients by visually analyzing their chest x-ray images. In our project, a new ML method is proposed to classify the chest x-ray images into two classes, COVID-19 patient or non-COVID-19 person. ML has demonstrated high performance for several image processing applications such as image analysis, image classification, and image segmentation. Presently, there are two main methods for testing COVID-19 namely, Molecular test and Serological test. COVID-19 tests are new, and assessing their accuracy is challenging. PCR tests may produce false negatives. Apart from clinical procedures, machine learning will provide a lot of support in identifying the disease with the help of image data. The proposed method of COVID-19 x-ray image classification model begins by extracting the features from the input images, either COVID-19 or Non-COVID-19, using feature extraction technique and Machine Learning Algorithms are used to classify the chest X-ray images. In addition, our proposed model will also analyze the severity of the affected COVID-19 class. The proposed diagnosis will be cost-effective and more accurate than standard tests for COVID-19.

This paper present about the performance of the waste water treatment of sample water of lake located in Anekal - taluk and its various components. With an increase population in the city of Karnataka there has been a huge demand of water which has created heavy havoc in the surrounding area of the city. With concern of the city’s people and environment we are treating water with natural coagulant which are environment friendly and cheaper as compared to the chemical coagulant. Generally, for drinking water treatment protocols consist of two steps that is coagulation/flocculation and disinfection. Commonly alum (aluminum sulphate) is used as coagulation agent, We are treating water with hyacinth peel powder, orange peel powder and banana pith powder which is naturally occurring vegetable and fruit-based powder. The result was analyzed using jar test and experimental work of rapid mixing speed at 120 rpm for 2 minutes and slow mixing speed at 30 rpm for 30 min and settling time of 30 min. The hyacinth peel is being extracted using distilled water and 1M of NaCl. powder extract from distilled water effectively removes turbidity about 90% and other chemicals with the optimum dosages of 3 gm/L. hence, this study demonstrates the potential of hyacinth peel powder to treat the waste water. The orange peel is being extracted using distilled water and 1M of NaCl. powder extract from distilled water effectively removes turbidity about 20% and other chemicals with the optimum dosages of 30 gm/L. hence, this study demonstrates the potential of orange peel powder to treat the waste water. The banana pith is being extracted using distilled water and 1M of NaCl. powder extract from distilled water effectively removes turbidity about 50% and other chemicals with the optimum dosages of 10 gm/L. hence, this study demonstrates the potential of banana pith powder to treat the waste water.