Daily Archives: January 4, 2024

Topological Insulators: A Review
Authors:Assistant Professor Mr. Vivek, Dr. Manoj Kumar Mittal

Abstract- Topological insulators represent a novel class of materials that have garnered significant interest in both theoretical and experimental condensed matter physics. This research paper provides a comprehensive overview of topological insulators, covering their theoretical foundations, unique properties, and potential applications. We begin by introducing the theoretical framework of topological band theory, which underlies the emergence of nontrivial electronic band structures in these materials. Through a detailed discussion of topological invariants and symmetry-protected topological phases, we elucidate the mechanisms responsible for the robustness of surface states and their protection against disorder and perturbations. Moreover, we explore the experimental realization of topological insulators in various material systems, ranging from semiconductors to topological crystalline insulators and beyond. The paper also examines the exotic electronic phenomena exhibited by topological insulators, such as the quantum spin Hall effect, topological surface states, and Majorana fermions. Furthermore, we discuss potential applications of topological insulators in fields such as spintronics, quantum computing, and low-power electronics. By synthesizing theoretical insights with experimental advancements, this paper aims to provide a comprehensive understanding of topological insulators and their significance in the realm of condensed matter physics.

DOI: 10.61137/ijsret.vol.10.issue1.199

Published by: Kajal Tripathi

Authors:- M.Siva Leela, Shaik Hussain Vali

Abstract-In this study, we use a loop matrix to describe the reorganisation of the RDN's formulation. Calculation time is increased when an optimum reorganisation is determined analytically. More network buses means more time to calculate. Therefore, a technique of optimisation is required to determine the best reorganisation of the radial distribution system. The optimum reorganisation aims to reduce network losses to a minimum. Genetic algorithm (GA) and particle swarm optimisation (PSO) are the optimisation methods employed in this piece. In this piece, we look at how meta-heuristic optimisation may be applied for efficient rearranging. For the purpose of rearrangement, we use organic optimisation techniques such as the PSO approach. We describe and analyse the reorganisation issue in a typical large-scale 119 and 135-node network under both optimisation and non-optimization conditions. The outcomes are then compared with one another.

DOI: 10.61137/ijsret.vol.9.issue6.117

Published by: vikaspatanker

Microbial Farming: Harnessing Soil Microbiomes for Sustainable Agriculture
Authors:Saba Rana, Vipin Kumar Saini, Vikas Kumar, Ankit Kumar, Ashu Chaudhary, Zehra Husaini

Abstract- Microorganism’scontributions to disease prevention, nutrient cycling, soil health, and plant growth promotion, microorganisms are essential to sustainable agriculture. Biocontrol agents, mycorrhizal fungi, and rhizobacteria that promote plant development are examples of helpful microorganisms that can be used as environmentally benign and sustainable substitutes for traditional farming methods.Pesticides and chemical-based fertilizers are widely used to boost yields from agriculture in order to meet the nutritional needs of the world’s growing population. However, careless pesticide usage has contaminated the environment and put public health at risk. Furthermore, the quality and physical characteristics of agricultural soils, together with their chemical (nutrient imbalance) and biological health, are progressively deteriorating. Furthermore, the integration of farm-gate nutrient balance assessments and tailored fertilization plans can optimize nutrient use efficiency, reduce environmental impacts, and ensure long-term soil fertility. This paper emphasizes the need for sustainable agricultural practices that harness the power of microorganisms to improve productivity while minimizing environmental harm.

DOI: 10.61137/ijsret.vol.10.issue1.198

Published by: Kajal Tripathi

Authors:-Dr. Juhi Shamim

Abstract- Present paper discusses the determinants of food grains production in India. The Indian economy has changed fundamentally over time with the foreseen decrease in agriculture’s share in gross domestic product (GDP). There is high burden on agriculture to produce more and to raise the income of farmers. India’s manufacturing sector saw unpredictable growth and its share in GDP has nearly stayed steady at 15 percent over the most recent three decades. Under these conditions, it is valuable to investigate the determinants of agriculture growth. There are countless determinants that influence food grains production. Some of them are discussed in this paper.

DOI: 10.61137/ijsret.vol.9.issue6.116

Published by: vikaspatanker

Polyhouse Technology and Its Application in Modern Agriculture
Authors:Assistant Professor Sachin Sharma

Abstract- The field of agriculture has undergone substantial evolution to incorporate innovative techniques, with polyhouse farming emerging as a sophisticated method. Polyhouses serve as a means to cultivate crops in precise environmental conditions. This research paper is dedicated to exploring the intricacies of polyhouse farming, including its various construction types, practicality, advantages, disadvantages, and its role in promoting sustainable agriculture. Furthermore, it delves into the diverse applications of polyhouse farming, spanning from vegetable cultivation to flower production and the cultivation of medicinal plants. The paper also delves into the challenges associated with polyhouse farming, such as the need for significant investments and technical expertise, while also providing recommendations to enhance its effectiveness in various agro-climatic regions.

DOI: 10.61137/ijsret.vol.10.issue1.197

Published by: Kajal Tripathi

 

Srinivasa Chakravarthy Seethala
Affilation:	Senior Data Engineer HCL America Inc, USA
Email-Id:	srinivasa.seethala@gmail.com
About Srinivasa Seethala has done Bachelor of Engineering in Mechanical from University of Madras. A Senior Data Engineer with over 25 years of experience, specializing in AI, Big Data, and data warehousing development. I have demonstrated expertise in designing and implementing advanced data solutions, integrating AI to enhance data quality and system performance. A recognized leader in the field, I excel at modernizing data architectures and leading cross-functional teams to deliver innovative solutions for complex challenges. As a published author with expertise in AI and Big Data, I am skilled at driving impactful projects across industries, including finance, healthcare, and e-commerce, while ensuring scalability and efficiency in data systems.
Projects & Publications: PNC Claims(Snowflake) Client: United Services Automobile Association (USAA) Project : Project OAK Client: United Technologies Corporation, USA Project : Broker Dealer Operations Reporting Client : Lincoln Financial Group, USA

 

Published by: vikaspatanker