International Journal for Global Academic & Scientific Research
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Women empowerment with educational tools special references on tribal girl education in selected districts of Uttarakhand
Full text linkEducation is essential to the development of the society, therefore it is included in formulation of HDI as education index. HDI was developed in order to assess development of a nation considering life expectancy, education and standard of living. Education contributes to change the mentality of the people to the right direction and helps to control the increase population birth of the country by given the proper knowledge and information about the society and world. Education also enhances the empowerment among the women. The study will assist the policy makers to develop promising strategies and take measures that will minimize hindrance of SC/ST and female education and enhance the enrolment of both SC/ST and female in education
Transforming human resource management with HR analytics: A critical Analysis of Benefits and challenges
Full text linkHuman resources have long been a valuable organizational asset. Employees must be considered as resources to gain a competitive edge, and firms may survive in a competitive market by aligning human resources with essential business objectives. Organizational success has always revolved around human resources. The alignment of HR strategy with the company\u27s overall strategy relies heavily on personnel analysis. Human resource analysis aids HR managers in developing strategies that will allow the company to outperform its competition. The revolution and difficulties of human resource management using hr analytics are examined in this study. Human resource analysis (HR) has the ability to greatly improve HR departments\u27 decision-making capabilities in human and organizational capital. Sample of 217 respondents from HR team of different organizations were surveyed to know the benefits, challenges and impact of Transforming Human Resource Management with HR Analytics. It is found that there is a significant impact of transforming human resource management with HR analytics in an organization
A Study on Data Scaling Methods for Machine Learning
Full text linkMachine learning (ML), a computational self-learning platform, is expected to be applied in a variety of settings. ML, on the other hand, uses a model built with a learning structure rather than traditional code that is written line by line in a continuous pattern. These models are created and equipped to determine the results of training using historical data. Scalability is a major challenge in real machine learning programs. Many ML-based technologies are essential to quickly analyze new data and create forecasts, as forecasts become meaningless after a few ticks (think real-time methods such as stock markets and clickstream data). Many machine-learning programs, on the other hand, need to be able to scale and train with gigabytes or terabytes of data during model training (As is found in the model from a web-scale image corpus). High-dimensional challenges pose new obstacles to machine learning professionals who are increasingly interested in scalability as well as algorithm quality. Against the backdrop of the current situation, this overview article on the scope of scalability in machine learning platforms collects, investigates, and analyzes the current state, aspects, and perspectives of scalability that can be added to machine learning platforms in a variety of ways to improve efficiency. The purpose is to do. Reliability when processing large amounts of data
A Review on Procedure of QSAR Assessment in Organic Compounds As a Measure of Antioxidant Potentiality
Full text linkoai:ojs2.journals.icapsr.com:article/2Chemical and biological properties of substances may be inferred from their more fundamental physical, chemical, and biological characteristics using QSAR models. An insilico model may be built using QSAR to anticipate the activity of novel molecules before they are synthesised, allowing the author to establish a quantifiable link between structure and behaviour. QSAR is a powerful tool. Although QSAR modelling is a computer area, medicinal chemists are the main users and ultimate assessors, especially when it comes to developing compounds with the necessary biological activity. Several studies were conducted in which medicinal chemists and cheminformaticians collaborated to discover new compounds with specific biological activity. This was done through the development of QSAR models and their use in virtual screening, followed by experimental verification. Despite the fact that QSAR methods have their own set of limitations, their use in molecular prediction and assessment has been effective due to a division of labour in which mathematical professionals ensured the greatest quality of models. The predictions also helped experimental chemists design and test compounds that were expected to be successful. This review is being developed and implemented to look into the development of the QSAR tool in the assessment of antioxidant potentiality for diverse organic chemicals found in our environment