Category Archives: Uncategorized

AI Revolution: Transforming Risk Management in Financial Institutions
Authors:-Kinil Doshi

Abstract-This article reviews the implications and enhancements that Artificial Intelligence may bring to financial institutions in terms of risk management transformation. In a dynamically evolving environment provided by the progressed state of AI technologies, the transformation solved becomes evolutionary more strategic. This paper examines the power of AI in improving the accuracy, efficiency, and transparency of risk assessments and management processes. A necessary focus is on AI’s possibility to process unlimited data in real-time, thus creating a new paradigm of proactive decision-making and risk assessment by identifying it early in the process. Apart from that, some potential applications such as credit assessment, regulatory compliance, and cybersecurity are also considered, since the latter issues are the field of a problem to institutions where major disruptive innovation is required. The challenges and the moral concern of AI are also discussed, including the pros and cons of data use and the compliance function. Overall, highlighting existing and potential use cases and forward-thinking trends allow for this article to see AI as vital since, in a developing industry, financial institutional survival is impossible without it.

DOI: 10.61137/ijsret.vol.10.issue2.291

Published by: Kajal Tripathi

Importance of Vedic Mathematics in India
Authors:-Anjali Goyal, Vinit Kumar Sharma

Abstract-Vedic Mathematics is a powerful system of mathematics based on ancient Indian principles, offering efficient and solving complex mathematical problems. Vedic Maths is important for Increases Calculation Speed, Improves Mental Math Skills, Simplifies Complex Problems, Boosts Confidence and Reduces Math Anxiety, Enhances Problem-Solving Skills, Helps in Competitive Exams, Develops Logical and Analytical Thinking, Improves Overall Mathematical Understanding,promotes a Deeper Connection to Ancient Knowledge& Boosts Academic Performance.

DOI: 10.61137/ijsret.vol.10.issue2.298

Published by: Kajal Tripathi

Scopes and Advances of Nano-fertilizers in Agricultural Development
Authors:-Vipin Kumar Saini, Disha Sharma, Saba Rana, Ashu Chaudhary, Vikas Kumar

Abstract-The overuse of fertilizers in agriculture to boost yields has been shown to be wasteful because most of them are wasted and have detrimental impacts on both the environment and human health. With the goal of lowering the usage of mineral fertilizers, raising yields, and promoting agricultural development, farmers face a significant barrier in substituting the application of fertilizers with nanofertilizers. An extensive summary of the effects of nanofertilizers on the environment is given in this review. A review and description are given on the use of nanofertilizers and novel delivery systems to increase agricultural productivity. The benefits of the nanoencapsulation technology are highlighted specifically for fertilizers. Nanomaterials can encapsulate micro- or macronutrients in nanofertilizers, allowing for the regulated and slow release of nutrients into the soil to preserve soil fertility and avoid eutrophication and water resource contamination. For the proper and secure use of nanofertilizers in agriculture, a risk assessment is necessary.

DOI: 10.61137/ijsret.vol.10.issue2.296

Published by: Kajal Tripathi

NIRBHAY: Analysis and Prediction of Crime
Authors:-Ms. Sayali Angat, Mr.Kapil Gharat, Mr.Angarak Gurav, Ms. Harshala Patil, Professor Prachi Sorte

Abstract-The increasing complexity and scale of urban areas requires new crime analysis and prediction strategies The research project focuses on harnessing the power of machine learning algorithms to analyze historical crime data and predict future crime in specific areas. This study explores the potential of predictive analytics for crime prevention and law enforcement using clinical data that includes various crime types, demographic data, and characteristics of the area. This approach involves pre-processing the dataset to resolve missing values, outliers, and feature engineering to extract relevant information. To find patterns and correlations between variables, a range of learning models such as support vector machines, random forests, and decision trees are fed into the data. Utilize measures like accuracy, precision, recall, and F1 score to assess the performance of the model. Furthermore, the actual offense is incorporating predictive models into internet platforms in order to allow users to get predictions based on characteristics like time, location, and publicly accessible data. The platform provides law enforcement, legislators and urban planners with information to better allocate resources and prevent crime. The results demonstrate the effectiveness of the machine learning process in crime analysis and prediction, with high accuracy in predicting crime scenes. The use of the website promotes easy access and usability, providing participants with the skills to reduce crime and increase public safety in the city.

DOI: 10.61137/ijsret.vol.10.issue2.140

Published by: vikaspatanker

Unveiling the Complexities of Behavioral Finance: Understanding Human Decision Making in Financial Markets
Authors:-Preeti Padma Sahu, Aniket Burman

Abstract-Behavioral finance is a subject of finance that studies the impact of psychological factors on how people make financial choices. This study intends to make valuable contributions to the expanding body of research in behavioral finance by exploring the behavioral biases and heuristics that affect investors’ decision making processes. Through a comprehensive review of existing literature, key concepts such as loss aversion, overconfidence, and herding behavior are examined, providing insights into the irrational behavior observed in financial markets. The objective of this research is to empirically analyze the impact of behavioral biases on investment decisions using a mixed methods approach combining qualitative and quantitative analysis. Data is collected through surveys and interviews with investors, supplemented by quantitative analysis of market data. The findings reveal significant correlations between certain behavioral biases and investment outcomes, shedding light on the complexities of human behavior in financial decision making. The conclusions drawn from this study underscore the importance of understanding and mitigating behavioral biases to enhance investment performance and promote financial wellbeing. This research contributes to both theoretical understanding and practical applications in the field of behavioral finance, offering valuable insights for investors, financial practitioners, and policymakers alike.

DOI: 10.61137/ijsret.vol.10.issue2.139

Published by: vikaspatanker

Social Media’s Impact on Food Industry
Authors:-Palak Sinha, Mohd. Faisal, Krishna Rajput, Ms. Tanya Sharma

Abstract-This in-depth analysis examines the profound impact that social media has had on consumer behavior and how it has changed the food industry. The unique connection between advanced stages and the culinary scene is analyzed, featuring the crucial job of virtual entertainment in forming dietary inclinations, dietary patterns, and feasting decisions. The review researches the meaning of client created content, powerhouse advertising, and arising advancements in reshaping the food environment, with suggestions for nourishment, culinary culture, and monetary strengthening. Tending to scholastics, industry experts, and policymakers, this paper offers important bits of knowledge into the developing computerized age food industry.

10.61137/ijsret.vol.10.issue2.138

Published by: vikaspatanker

Effect of Guided-Inquiry Teaching Method on Academic Performance of Philippine Public Secondary School Grade 12 Students: A Quasi-Experimental Research
Authors:-Jomar P. Flores, Nivea Louwah D. Sermona

Abstract-This study investigated the effect of the guided inquiry teaching method on the academic performance of Philippine public secondary school grade 12 students in Electrical Installation and Maintenance. A quasi-experimental design was adopted for the study. A pre-test and post-test were conducted for both control and experimental groups. The instruments used for data collection were 30 objective questions tagged as the Electrical Installation and Maintenance Achievement Test (EIMAT). The instrument was validated by five experts in the field. To determine the instrument’s reliability, Cronbach’s alpha formula was used and a reliability coefficient of 0.84 was obtained. Means and standard deviations were used to analyze the descriptive data, while the null hypothesis was tested using a t-test at a 0.5 level of significance. Findings revealed that students taught with the guided-inquiry teaching method performed better with higher post-test mean scores than those taught using the lecture-demonstration teaching method. Also, findings indicated that the guided-inquiry teaching method makes the students perform better in terms of their performance skills than the lecture-demonstration teaching method. Given the findings, it was recommended, among others, that the guided-inquiry teaching method be adopted in technical colleges and secondary schools for instruction in EIM to improve the academic performance of the students.

DOI: 10.61137/ijsret.vol.10.issue2.137

Published by: vikaspatanker

Evaluation of Strength Properties in Geopolymer Bricks Blended with Rice Husk Ash and M Sand
Authors:-Kavipriya S, Kamalini V, Kanishkaa C, Amala P

Abstract- This paper presents a parametric experimental studies which investigate the effects of using geopolymers (such as fly ash and alkaline activator solution), rice husk ash, M-sand and sawdust in the production of bricks. This project mainly focus towards the production of unburnt bricks to replace normal conventional burnt clay bricks and this could be achieved by polymerization process under ambient curing conditions. This product enhance in reduction of ecological pollution by reducing emission of CO2 concentration. Rice husk ash and saw dust are the organic wastes that can be recycled for use in construction industry without producing any harm to human and environment in a great manner. Size of bricks to be casted is about 22 x 7.5 x 7.5cm. Both strength and durability properties such as compressive strength, water absorption, efflorescence tests are to be carried out in this project to check the reliability of geopolymer bricks with normal conventional bricks and flyash bricks.

DOI: 10.61137/ijsret.vol.10.issue2.301

Published by: Kajal Tripathi

Opportunities and Threats in a Smart Grid Setting for AI-Enabled Demand Response
Authors:-Ryan Ed

Abstract-One of the most essential commodities for modern humans is electricity. The notions of smart grids with demand response were established to tackle problems and obstacles in the transfer of power via the conventional grid. Wind turbines, microgrids, and defect detectors are just a few of the power generating, transmission, and distribution components that contribute to the massive amounts of data produced everyday by these systems. Smart electric appliances and meters also play a role in load control. New developments in computers and big data have made it possible to use Deep Learning (DL) to forecast electrical consumption and peak hours by discovering patterns in the produced data. Inspired by the potential benefits of deep learning for smart grids, this article aims to provide a thorough overview of how DL is being used for intelligent smart grids with demand response. Here we lay down the groundwork for deep learning, smart grids, demand response, and the reasoning behind all of this. Second, we take a look at the most recent developments in deep learning’s use to smart grids and demand management, including topics like electric load predicting, state estimation, energy theft identification, energy sharing, and trading. Furthermore, we demonstrate the usefulness of DL via a range of applications and use scenarios. Lastly, we draw attention to pressing concerns and possible future possibilities in the application of DL to smart grids and demand response, as well as the difficulties already encountered in the literature.

DOI: 10.61137/ijsret.vol.10.issue2.159

Published by: Kajal Tripathi

Strategic Data Management: Frameworks, Implementation Challenges, and Success Stories
Authors:-Jorge White

Abstract- In the current landscape where digital innovation shapes every aspect of business operations, the adept management and strategic use of data stand as pivotal factors in securing organizational prosperity and a competitive edge. This study ventures into the realm of data strategy, shedding light on its pivotal role in the digital age and its profound influence on the operational dynamics of contemporary organizations. It outlines a variety of methodologies for the formulation of a holistic data strategy, encompassing essential facets such as governance, data quality, architectural integrity, and organizational data literacy. Furthermore, this research identifies prevalent obstacles encountered during the deployment of data strategies and furnishes actionable strategies derived from the successful experiences of leading organizations. By engaging in a comparative scrutiny of diverse strategic models and probing into the avant-garde trends shaping data management, this paper prognosticates the trajectory of data strategy evolution and its repercussions for future business models. Offering an amalgam of theoretical constructs, empirical challenges, and illustrative success narratives, the paper serves as a comprehensive guide for entities aiming to optimize their data strategy endeavors, thereby maximizing the utility of their digital information reservoirs.

DOI: 10.61137/ijsret.vol.10.issue2.136

Published by: vikaspatanker