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Focus of Budget 2018-19

http://www.jimsgn.org/ Focus of Budget 2018-19 The key focus of the Budget 2018-19 is on strengthening the rural economy and reviving up growth in the rural sector. To that end a slew of measures have been announced in the Budget which among other include higher MSPs for kharif crops, upgradation of rural haats to give farmers better access to formal mandi, increase in institutional farm credit, new funds for Fisheries and Animal Husbandry sectors, more fund for re-structured National Bamboo Mission fund, allocation for deprived irrigation districts, extension of the facility of Kisan Credit Cards to fisheries and animal husbandry farmers to help them meet their working capital needs. All these measures would transform rural India in a big way. For the benefit of lower and middle class the measures like increase in loans to Woman Self Help Groups, higher targets for Ujjwala, Saubhagya in providing free LPG connections, electricity and toilets have been announced.  These meas

Introduction to Screen less Displays with Their Types

  Screen less displays are an emerging technology that aims to present visual information to users without relying on conventional screens. Unlike traditional display systems, which use screens as an interface for visual interaction, screen less displays project or communicate visuals directly onto the air, human eyes, or a surface, making the viewing experience more immersive and, in some cases, more practical. This technology is particularly significant as it offers possibilities for more integrated and portable computing experiences, potentially eliminating the need for bulky monitors, tablets, or smart phone screens. Screen less displays have applications in industries ranging from healthcare and automotive to education and gaming. The types of screen less displays can generally be divided into three main categories: visual image, retinal direct and holographic displays. Each of these has unique characteristics and applications. 1. Visual Image Displays Visual image displays

Ubiquitous Computing: The Future of Seamless Integration

  Introduction Ubiquitous computing, often referred to as "ubicomp," represents the concept where computing is seamlessly integrated into everyday life, so much so that it becomes invisible. Unlike traditional computing, which requires direct user interaction with a device like a desktop or laptop, ubiquitous computing aims to embed computers into the environment, making them available anytime and anywhere without being overtly noticeable. This technological shift has profound implications on how we interact with the world around us, shaping industries, transforming user experiences, and raising critical ethical and societal questions. The term "ubiquitous computing" was first coined by Mark Weiser in 1988 at Xerox PARC. Weiser envisioned a future where computing devices were embedded in objects and spaces, enabling them to communicate, collect data, and offer services without requiring a user’s active engagement. At the time, Weiser’s vision seemed far-fetched, but

Advanced Technologies of Business Intelligence

  Business Intelligence (BI) has transformed with the advent of advanced technologies, enabling organizations to harness the power of data more effectively. These technologies not only streamline data processing but also enhance decision-making by providing deeper, more actionable insights. Here’s a look at the key advanced technologies shaping BI today: 1. Artificial Intelligence (AI) and Machine Learning (ML) Artificial Intelligence is revolutionizing BI by automating and enhancing data analysis. AI-driven analytics allows businesses to detect patterns, anomalies, and insights in data that may not be visible through traditional methods. Machine Learning (ML) models enable predictive and prescriptive analytics, helping organizations forecast future trends and make data-driven recommendations. ML continuously improves with the data it processes, delivering increasingly accurate predictions. Natural Language Processing (NLP) further enables BI platforms to respond to natural language

BBA- your first step to business world

  The world is changing faster than ever before and with this fast changing world one needs knowledge, skills and adaptability. No matter your academic and intellectual level, it’s important to continuously  learn and adapt to changes happening in corporate and industries. Nobody can get success easily without learning new skills and knowledge.  Now the question comes how can a student fresh out of school can aspire to be successful manager or corporate person? The answer is enrolling oneself in a professional management course like BBA from an esteemed institution equipped with best faculties, modern amenities along with good infrastructure and facilities.  The study of BBA will provide you with the tools and skills needed to land leadership positions, head up your own company, as well as manage teams, individuals, and organizations effectively. Studying BBA will also position you for outstanding earning potential. Let us get down to understand extensively how BBA proram helps advance

Top 5 Jobs after a B.Tech in Data Science & Artificial Intelligence

  After completing a B.Tech in Data Science and Artificial Intelligence , graduates are well-equipped to enter a rapidly evolving job market. The skills acquired during this program open doors to a variety of exciting and lucrative career paths. Here are the top five jobs that you can pursue: 1. Data Scientist Role Overview : Data scientists are tasked with analyzing complex data sets to extract actionable insights. They use statistical techniques and machine learning algorithms to build predictive models that can drive business decisions. Key Responsibilities Collecting and cleaning data from various sources. Performing exploratory data analysis to identify trends and patterns. Developing models that can forecast outcomes based on historical data. Skills Required : Proficiency in programming languages such as Python and R, knowledge of statistics, machine learning algorithms, and data visualization tools like Tableau or Matplotlib. 2. Machine Learning Engineer Role Overview : Machine