Indian Textile Industry is one of the leading textile industries in the world. The economic liberalization of Indian economy in 1991 gave the much needed thrust to the Indian textile industry, which has now successfully become one of the second largest in the world. There are many states like West Bengal, Tamil Nadu, Gujarat, Kerala and Maharashtra which are textile hub of the Country. Among them Maharashtra is one of the giants in the textile manufacturing and also the one to owe highest industrial outputs in the textile sector. There are abundant natural resources, skilled manpower and premiere R&D centers. Additionally bulk of raw material available is all responsible for pushing down the cost of textile industry. Due to all these favorable factors, it co ntributes highest FDI in the country and highest contribution to India’s GDP. This industry comprises of both Public and Private sector textile units. Though it is leading textile producing state but it is struggling hard to uphold and maintain its position. Therefore, it is important to check the financial health of Public sector textile units in Maharashtra. In the present study researcher has identified various significant ratios to evaluate and predict the financial health of selected public textile units with the help of Altman’s z score model.

Behavioral theories are viewed as a relatively new phenomenon in the security markets. Therefore, examining the subject is essential in order to understand the changing world of investments. Current technology enhances fast trade between individual investors. The concept of investing is seen as trendy. Therefore, people tend to make illogical decisions not based on true knowledge or information of a certain investment object. These decisions are explained via several behavioral finance theories. The outcome of poor knowledge is that investors allow these theories to effect on their decision-making process, thus resulting in major losses. The behavioral models can affect on individuals’ decision-making whether actual investments are conducted via professionals or not. The concept of investing is extensive as it can include all the aspects of purchasing items expected to gain more value in the future (art, antique, securities etc.). Therefore, it has been decided to narrow down the subject to concentrate on stock trading and the impact of behavioral finance on individual portfolio investors.

This research paper attempts to highlight a new perspective on the study of behavioural finance. In this study, the aim is to establish the existence of such fundamental issues, driven by various psychological biases, in the investment decision-making process. Behavioral economists firmly believe that psychological factors influence investment decisions. They argue that today’s investment decisions demand a better understanding of individual investors’ behavioral biases. However, many economists believe completely in the application of traditional theories in the decision-making process and hence do not consider the concept of irrational behavior.  Behavioral finance therefore studies the influence of psychology on the behavior of portfolio investors and their consequent reactions in stock market investing. In this context, it seems relevant to check whether the behavioral factors have an influence on the decision-making process of portfolio investors. A questionnaire will be formulated and distributed among the clients of two brokerage firms in India and their investment decisions and effects of behavioral factors on it will be studied. The focus is on individual investors as they are more likely to have limited knowledge about application of traditional theories in decision-making and hence are prone to making psychological mistakes. The primary analysis would be focused on determining whether behavioral factors affect the investors’ decision to buy sell or hold stocks.

Database emerged as a big and important field in software development nowadays and use of database is increasing day by day. The use of database is increasing with the passage of time and the security & privacy issues of data in the database are also increasing so different techniques are emerging to tackle these issues . Data masking is the process of de-identifying (masking) specific data elements within data stores. The main reason for applying masking to a data field is to protect data that is classified as personal identifiable data, personal sensitive data or commercially sensitive data, however the data must remain usable. There are variety of situations in which users, developers or other personnel may not be allowed to view information that they are not authorized to see such as in development phase, training sessions, testing etc. Many methods are used for data masking such as substitution, shuffling, variance, encryption, nulling out, field masking etc. Data masking is a technique used to hide the original data from developers and end users in development process and training sessions.

Behavioural finance theories explain "why" individuals exhibit behaviours that do not maximize expected utility. Behavioural finance highlights inefficiencies, such as under- or over-reactions to information, as causes of market trends and, in extreme cases, of bubbles and crashes. Such reactions have been attributed to limited investor attention, overconfidence, over optimism, mimicry (herding instinct) and noise trading. Technical analysts consider behavioural finance to be behavioural economics' "academic cousin" and the theoretical basis for technical analysis.

This research work explores how anomalies in equity markets exist and there have been various discussions and arguments on this topic. It also researches the effect of these anomalies in the working of the equity stock markets in Indian context. This research expands on the research work of Shefrin [2000], who concluded through his research that recent stock market price changes exert a strong influence on risk tolerance attitudes and behaviours.

This present work emphasis on the improvement of resonant converter (DC –DC converter) for solar energy conversion system (SECS). It accentuations on plan and exhibiting periods of the distinctive constituents of the SECS like the rudimentary model of zero voltage switching (ZVS) converter, inverter, fuzzy logic controller, best maximum power point tracking (MPPT) system utilizing MATLAB/ Simulink. Here, a resonant converter represents the static and dynamic characteristics of an actual solar irradiance have been developed for simulation tests. The irradiance and temperature changes circumstances are performed using the resonant converter, which consist of PV system, whose control is implemented using Fuzzy logic control unit and MATLAB/ Simulink. This PV module can achieve maximum power using Perturb & Obserb algorithm. Under various abnormal conditions like change in irradiance and temperature, step change in irradiance etc. The control system is executed on a fuzzy logic control unit. Speculative outcomes are exhibited utilizing a 200W model of SECS to demonstrate the better aftereffects of the propelled framework and their control under steady- state and dynamic conditions.