Volume 9 | Issue 10 |

 Abstract

According to the World Health Organization (WHO), the seventh major cause of human death in 2030 will be diabetes, which of course is a very severe disease and if not treated thoroughly and on time, can lead to critical problems, including death. Millions of people are affected by the disease. The risk of diabetes is increasing day by day and is found mostly in women than men. The diagnosis of diabetes is a tedious process. Diabetic retinopathy is a disease caused by uncontrolled chronic diabetes and it can cause complete blindness if not timely treated. Therefore early medical diagnosis of diabetic retinopathy and it medical cure is essential to prevent the severe side effects of diabetic retinopathy. Manual detection of diabetic retinopathy by ophthalmologist take plenty of time and patients need to suffer a lot at this time. So with improvement in science and technology it is made easy to predict the disease. The purpose is to diagnose whether the person is affected by diabetes or not using classification based machine learning technique. This paper reviews, classifies and compares the algorithms and techniques previously proposed in order to develop better and more effective algorithms.

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 Keywords

WHO, Diabetic Retinopathy, Classification based Machine Learning techniques, Algorithms

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 Abstract

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Culture, Naga, tradition, Christianity, Change

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Creative Commons Attribution 4.0 and The Open Definition

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This review comprises of the chemical formulations, fundamental and technical aspects of the complete acid zinc plating process. The review discusses the effect of physical and chemical plating parameters, brighteners, carriers and levelers on the throwing power of the plated product. In practice, there are several additives that are added to make an acid zinc plating process efficient. In this article, we talk about their influence solely on the throwing power. The effect of Tiron and SiO2 nanoparticles on the throwing power of acid zinc bath is also investigated in the article.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Electroplating, acid zinc plating, throwing power, nanoparticles, colloidal silica, tiron, additives

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Technical advancement has given a backseat to the writing activity, but we cannot underestimate the importance of writing skills. Writing is the most difficult of the language skills. It is a skill in which we produce a sequence of sentences arranged in a particular order. It is a production skill involving, manipulating, structuring, and communicating, Learning to write in English is a mode of communication. In the present world scenario, whether you like it or dislike it, learning English has become mandatory to perform better and to march ahead in this competitive world. A teacher has to prepare the learner to develop their writing skill in real-life settings. But many times, this learning becomes examination-oriented. Learning to write is not just a natural extension of learning to speak a language. A close relationship between writing and thinking makes writing a valuable part of any language course. Writing is one of the most demanding skills, which has to be deliberately cultivated.

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Why are our Students Unable to Write in English

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Creative Commons Attribution 4.0 and The Open Definition

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KEYWORDS: Ocimum sanctum L., Ethanolic, E.Coli - Escherichia coli., Bacillus subtilis, Yeast - Saccharomyces cerevisiae, Microliter, Inhibitory concentration.

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COVID-19 is extremely infectious that spreads quickly from across the world, making early diagnosis critical. COVID-19 diagnosis is critical. Numerous investigations have been performed to ascertain if patients' chest X-rays, as well as computed tomography (CT), scans reveal COVID-19 infection. COVID-19 illness results on computed tomography (CT), as well as X-ray imaging, are like those of other lung infections, making it problematic for medical experts to differentiate COVID-19. The purpose of this research has been to determine the role of machine learning, deep learning, or pictures processing within fast or precise identification of COVID19 from two of the most frequently used medical imaging modalities, chest X-ray or CT pictures. We evaluated performance of ML and DL techniques on chest X-ray pictures as well as CT scans to COVID-19 diagnosis in this research. The proposed convolutional neural networks (CNNs) using the Alexnet Model for CAD of coronavirus from CT and X-ray pictures. The efficiency of this technique was checked on the data set obtained. We classified COVID-19 CT & X-ray scans as well as examined the evolution of the condition of the patients via CT scans. Accuracy of these techniques varied from 93.25 percent to more than 99.82 percent, suggesting that machines, as well as deep learning methods, apply to the clinical diagnosis of COVID-19. The trials carried out in this research have shown the efficacy of the pretrained COVID-19 alexnet model of CNN.

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 Keywords

COVID-19, Machine Learning, Deep Learning, CNN, Alexnet Model.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Lower Caste, Dalit, Sufferings

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Creative Commons Attribution 4.0 and The Open Definition

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Euglena is unicellular green algae with two flagella, belongs to the group euglenoids. It is found mostly in small fresh water pools rich in organic matter. These are grow luxuriantly in such waters imparting its colour, dark green to the water body. The present study reveals 28 species of Euglena. These are collected from various parts of Nashik and its tahsils. Among these Euglena acus var. rigida, E. limnophila var. minor, E. obtusa are reported new to India, Few taxa are also little known and appear as first reports for Maharashtra, these are Euglena rostrata, E. wangi .Rests are explored first time from this region. This enriches the algal flora of Nashik.

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 Keywords

Systematic account, Diversity, Euglenoids, Euglena, Nashik

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Creative Commons Attribution 4.0 and The Open Definition

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Automated computer-vision-based defect detection has received much attention with the increasing surface quality assurance demands for the industrial manufacturing It can be divided into colour analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users. An survey of automated defect detection and classification technique that can ensured the better quality of tiles in manufacturing process as well as production rate.

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 Keywords

Control, Defects Detection, Morphological, Quality, Segmentation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition