Abstract
The role of Public Sector Undertakings (PSUs) in the growth and development of Indian Economy never be overemphasized. PSUs have been played very significant role in designing diversified industrial base in India. As new industrial policy announced in 1991, Indian company have to face competition at global level. For that additional power given to some mega Central Public Sector Undertakings (CPSUs). In October, 2021 maharatna status given to Power Finance Corporation Limited. The present study have been made in order to evaluate the financial performance of Power Finance Corporation Ltd. from 2016-17 to 2020-21. For analyzing the data financial ratios and some statistical tools such as percentage, mean and correlation used. It is found in the study that 1. The relationship between Gross Profit and Sales of PFC is significant. 2. The relationship between Net Profit and Sales of PFC is significant. 3. The relationship between Net Income and Total Assets of PFC is significant. 4. There is a significant relationship between Earnings before Interest & Tax and Capital Employed of Power Finance Corporation Limited.

Abstract
In recent years, the use of Online Trading for Financial Assets is increasing because of the implementation of 4G network and Innovation in technology, especially Electronic networks, i.e., the Internet. Technology innovation provides quick & easy execution of the order. The process of purchase & sale of Financial Assets in an electronic form is known as Online Trading. By opening a trading account & with an Internet connection, anybody can purchase and sell the stock market securities. This paper explores the Investor's Perception towards online Trading for financial assets in Surat District. For this purpose, a structured questionnaire was prepared in the google form, and 146 respondents were surveyed in December 2021. For analyzing the data, chi-square goodness of fit test was used & it was discovered that demographical parameters like Age, Gender, Income, Education, Occupation and Marital status. on Investor's Perception towards online Trading for Financial Assets. For other calculations, the Percentage & Likert scale is also used. Furthermore, for better understanding, Ranking was provided to various factors that affect the investors' decision-making process. Rank was provided according to weighted scores & by analyzing the data the First Rank was provided to the factor Role of a financial adviser, The Second Rank was provided to the factor Past performance, The Third Rank was provided to the factor Risk & Return profile, The Fourth Rank was provided to the factor Tax consideration, and the Fifth Rank was provided the factor Brand. The Ranking was also provided to the factors considered before making an Investment by Investors. Rank 1 was provided to the factor Recent Price Moment in A Firm's Stock, and Rank 2 was provided to the factor Past Performance of The Firm's Stock, Rank 3 was provided to the factor Stock Marketability, Rank 4 was provided to the factor Government Share Holdings in The Company, Rank 5 was provided to the factor Reputation of the Firm & Rank 6 is provided to the factor Rumours.

Abstract
Twitter is the most generally used micro blogging and social media platform for expressing ideas. Today's society makes it challenging to analyses Twitter sentiment. In the area of opinion mining research, the utilization of sentiment classification for the English language has increased in popularity. It is still based research on specific Indian languages, and progress is really slow. In this paper, we present a useful technique for evaluating the sentiment of Gujarati tweets on Twitter. This analysis is used to determine and classify Gujarati tweets into three classes (Positive, Negative and Neutral). We concentrate on extracting features and word identification because pre-processing methods improve classification accuracy.

Abstract
The corona virus illness 2019 (COVID-19), which began out on the stop of 2019, had a sizeable impact on the arena and keeps to pose a chance to human health. It's none the less going study in numerous international locations and has value a variety of lives and property. In this study, we describe a Deep Conv-Dilated Net-primarily based totally method for finding and diagnosing Pneumonia in chest X-ray (CXR) pictures. Faster R-CNN with tiers is used because the community's structure. To keep the deep capabilities and positional records of the object, the Feature Pyramid Network (FPN) is merged into the final neural community of a dilated bottleneck. When given affected person X-rays, deep getting to know model automation the process and assure prompt, skilful, and ready results. After the picture is fed thru a sequence of convolutional and max pooling layers which might be activated via way of means of the usage of the ReLU activation function, that is then fed into the neurons gift withinside the dense layers, and finally, the output neuron is activated via way of means of the sigmoidal function, the classification takes place. As the version improves and decreases loss on the identical time, accuracy rises. By acting facts augmentation earlier than becoming the version, overfitting is avoided. Thus, the recommended deep learning model produce powerful and persuasive outcomes.

Abstract
In this world of data and information, big data becomes blessing in every sector. Technology of data analysis is becoming more and more useful in every filed and space science is not an exception of it. For getting accurate information of deep space, now scientists are looking into the big data technology for analysis of complex data of light rays. In this paper an example of Black hole image is taken for understanding purpose. This paper illustrates the complexity of space and uses of Big data technology in study of the deeper space.