Category Archives: Uncategorized

Laws and Regulations of Waste Management on Environment Protection and 3R’s
Authors:-Assistant Professor Mohd Nayeem Ali, Assistant Professor Anjali Jakhar, Assistant Professor Vikrant Kumar, Assistant Professor Aabid Ahmad, Assistant Professor Parveen Malik

Abstract- India has published its ‘National Policy on environment’ in 2006 for protecting and conserving critical ecological systems and resources. The State is not an absolute owner, but a trustee of all natural resources, which are by nature meant for public use and enjoyment, subject to reasonable conditions, necessary to protect the legitimate interest of a large number of people, or for matters of strategic national interest There are global challenges effecting Global environment are climate change, stratospheric ozone depletion, and biodiversity loss. To combat the environment challenges all the countries have evolved the 3R’s.The 3R’s principle are Reduce, Reuse, Recycle. The aim of this paper is to study the laws and regulation of some of the developed countries which follow the 3R’s and to know whether the Indian legal framework is at par with the developed countries or is there scope for further improvement for better environment protection.

DOI: 10.61137/ijsret.vol.9.issue4.341

Published by: Kajal Tripathi

Effect of Solid Waste on Climate Change- A Review
Authors:-Assistant Professor Vikrant Kumar, Assistant Professor Mohd Nayeem Ali, Assistant Professor Anjali Jakhar

Abstract- Environmental science plays an important part in our daily life. It helps in solving the various issues which are arising in the environment very rapidly and without the checks. It is a burning topic at present. The objectives of the study are to know the global warming, climate change, environmental pollutions and solid waste management. This research is fully based on the secondary data. In this research I analyses the causes and their effects of environmental issues on human beings as well as on plants. I relies that these environmental issues has become a threat to everything and everyone on earth. In environmental issues, each country’s own contribution to worldwide emissions is small so that to solve global environmental problem one needs coordinated actions between countries.

DOI: 10.61137/ijsret.vol.9.issue4.340

Published by: Kajal Tripathi

Decentralized Finance (DeFi): Reshaping Indian Financial Systems
Authors:-Associate Professor Dr Ashfaq Ali

Abstract- Decentralized Finance (DeFi) has emerged as a disruptive force in global financial systems, offering alternatives to traditional banking through blockchain-based solutions. This paper explores the role of DeFi in reshaping India’s financial landscape, focusing on its potential to enhance financial inclusion, streamline cross-border transactions, and democratize investment opportunities. Despite significant opportunities, challenges such as regulatory uncertainty, technological barriers, and financial risks hinder its adoption. The paper provides an in-depth analysis of these issues and offers recommendations for leveraging DeFi to transform Indian financial systems.

DOI: 10.61137/ijsret.vol.9.issue4.339

Published by: Kajal Tripathi

Authors: Srinivas Goud Thadakapally

Abstract: As the aging population grows rapidly, the need for smart home technology designed to assist the elderly in their daily lives, health care, and their overall quality of life is becoming more apparent. Although smart home systems have undergone remarkable technological developments, their use is still constrained in the face of concerns over usability, privacy, security, ethical issues, cost, and digital literacy. This paper is a user-centric study on the adoption of smart home that considers Technology Acceptance, ethical issues, and adoption issues related to older people. A thorough literature review is carried out to discover the main elements that affect the acceptance of the users and to analyze the existing smart home solutions. Moreover, a framework called User-Centric Smart Home Adoption Assessment (UCSHAA) is suggested, which assesses technology acceptance, ethical compliance, usability, privacy, and overall technology readiness for adoption. Examples of comparative analysis show that incorporating the principles of user centered design with the consideration of ethics can enhance trust, accessibility and adoption potential. The results offer guidance to researchers, developers, healthcare and policy makers in designing secure, ethical and user-friendly environments for the smart home to support healthy and independent aging. Future studies will aim at validating the proposed framework through large-scale studies in the real user environment.

DOI: https://doi.org/10.5281/zenodo.22268138

Published by: vikaspatanker

Authors: Vanaja Kumari Degala

Abstract: Early prediction of student academic performance has become an essential research problem in higher education due to increasing dropout rates and declining academic outcomes. The ability to identify at-risk students at an early stage enables institutions to implement timely interventions and personalized academic support. With the rapid growth of educational data, machine learning (ML) techniques have shown significant potential in extracting meaningful patterns from student records. This paper presents a comprehensive machine learning-based framework for early prediction of student academic performance using pre-admission data and first-year academic attributes. Several supervised learning algorithms, including Logistic Regression, Support Vector Machine, Random Forest, K-Nearest Neighbors, and Extreme Gradient Boosting (XGBoost), are evaluated. Dimensionality reduction using t-distributed Stochastic Neighbor Embedding (t-SNE) is employed to visualize high-dimensional student data. Experimental results demonstrate that combining admission scores with first-year course performance significantly improves prediction accuracy. The proposed approach can assist academic institutions in proactive decision-making to enhance student success and retention.

Published by: vikaspatanker

Authors: Hazel T. Richardson Assistant Professor, Audrey L. Hamilton, Stella J. Woods, Chaitanya Srinivas, Yashwanth kumar

Abstract: Enterprise organizations increasingly rely on large-scale, heterogeneous data generated from transactional systems, cloud platforms, Internet of Things (IoT) devices, business applications, and external data sources to support operational processes, business intelligence, and artificial intelligence initiatives. However, maintaining the accuracy, consistency, completeness, and reliability of enterprise data remains a significant challenge due to the growing complexity, volume, and velocity of modern information ecosystems. Conventional rule-based data validation techniques often struggle to detect evolving anomalies, hidden data inconsistencies, and complex quality issues in real time, resulting in reduced analytical accuracy and increased operational risk. This paper proposes A Hybrid AI and Statistical Framework for Enterprise Data Validation and Anomaly Detection, which integrates statistical validation methods with artificial intelligence, machine learning, predictive analytics, metadata-driven governance, and automated anomaly detection to provide a comprehensive enterprise data validation solution. The proposed framework combines statistical techniques such as distribution analysis, correlation analysis, outlier detection, hypothesis testing, and confidence interval estimation with machine learning algorithms capable of identifying complex anomaly patterns, predicting potential data quality degradation, and continuously adapting to evolving enterprise environments. A centralized metadata repository, governance policies, and continuous monitoring mechanisms enhance data transparency, lineage, compliance, and automated decision-making while supporting scalable deployment across cloud-native and hybrid enterprise architectures. Intelligent validation workflows automate data profiling, quality assessment, anomaly classification, remediation recommendations, and governance reporting, significantly reducing manual intervention and improving operational efficiency. By integrating explainable artificial intelligence, adaptive learning, and predictive quality analytics, the proposed framework enhances enterprise data reliability, strengthens regulatory compliance, improves business intelligence, and provides a robust foundation for intelligent data management and sustainable digital transformation across modern enterprise information systems.

DOI: https://doi.org/10.5281/zenodo.22007466

Published by: vikaspatanker

A Deep Learning Based Approach for Heart Disease Classification using PCG Datasets
Authors:- Smita Waskale, Arjun singh Parihar , Manisha Kadam

Abstract- Heart related diseases presently pose one of the major threat worldwide. Heart abnormalities show a wide variation because of which accurate diagnosis becomes challenging. Phonocardigram (PCG) signals and their analysis has opened up a new paradigm in telemedicine. The abrupt fluctuations and the randomness of the PCG signals make them difficult to analyze and extract key parameters called features. Conventional Fourier techniques fail in this regard. In this paper, we have proposed a wavelet based technique wherein the discrete wavelet transform (DWT) have been used for the processing and feature extraction of the PCG signals has been done subsequently. The features extracted are energy, variance, entropy and standard deviation. The features extracted can be subsequently utilized for the classification of the PCG signals using the Conjugate Gradient Algorithm. The three categories of classified are: stenosis, regurgidation and normal. It has been shown that the proposed algorithm attains an accuracy of 93%.

Cite: Smita Waskale, Arjun singh Parihar , Manisha Kadam. “A Deep Learning Based Approach for Heart Disease Classification using PCG Datasets”. IJSRET Volume 9 Issue 4, July-Aug-2023.

 

Published by: vikaspatanker

Modeling and Analysis of Grid Connected Induction Generator for Wind Power Application: Review
Authors:-M. Tech. Scholar Mohit Kumar, Assistant Professor Harjit Singh

Abstract- Over the past few decades, there has been an increasing use of induction generator particularly in wind power applications. In generator operation, a prime mover (turbine, engine) drives the rotor above the synchronous speed. Stator flux still induces currents in the rotor, but since the opposing rotor flux is now cutting the stator coils, active current is produced in stator coils, and motor now operates as a generator, and sends power back to the electrical grid. Based on the source of reactive power induction generators can be classified into two types namely standalone generator and Grid connected induction generator. In case of standalone IGs the magnetizing flux is established by a capacitor bank connected to the machine and in case of grid connection it draws magnetizing current from the grid.

Cite: Mohit Kumar, Harjit Singh. “Modeling and Analysis of Grid Connected Induction Generator for Wind Power Application: Review”. IJSRET Volume 9 Issue 4, July-Aug-2023.

Published by: vikaspatanker

Enhancement of Micro-strip performance with improvement of antenna gain and feeding technique
Authors:- Pawan Kumar Nishad, Ashish Suryavanshi

Abstract- The goal of this observed is to design and analysis the Microstrip Patch Antenna which covers the Ultra Wide Band 3.1 to 10.6 GHz. This synopsis covers study of basics and fundamentals of microstrip patch antenna. A series of parametric study were done to find that how the characteristics of the antenna depends on its various geometrical and other parameters. The various geometrical parameters of the antenna are the dimensions of the patch and ground planes and the separation between them and it also includes the dielectric constant of the substrate material. The parametric study also contains the study of different techniques for optimizing the different parameters of antenna to get the optimum results and performance. This is a simulation based study. The design and simulation of the antenna is carried out using microwave Studio simulation software. Four antennas with different types of shapes were designed which cover the entire UWB range. The First designed antenna has two half circular patches which are overlapped to each other. A narrow rectangular slit is added to the patch to improve the performance of antenna.

Cite: Pawan Kumar Nishad, Ashish Suryavanshi. “Enhancement of Micro-strip performance with improvement of antenna gain and feeding technique”. IJSRET Volume 9 Issue 4, July-Aug-2023.

Published by: vikaspatanker

Authors: Santhosh Reddy BasiReddy

Abstract: Customer Relationship Management and enterprise workflow platforms increasingly rely on artificial intelligence to automate decisions related to customer engagement, compliance enforcement, risk evaluation, and operational prioritization across complex organizational environments. While AI-driven automation improves efficiency, consistency, and scalability, it also introduces ethical, legal, and governance challenges that traditional workflow systems were not designed to address. Automated decisions can directly affect customer rights, financial outcomes, regulatory compliance, and organizational reputation, making responsible AI integration a critical architectural and operational concern. This article examines ethical and responsible AI frameworks as they apply to CRM and business workflows, with particular emphasis on governance structures, human oversight mechanisms, transparency, and accountability. By synthesizing established standards, process modeling practices, and human-centered AI research, the paper proposes a structured framework for embedding ethical safeguards into enterprise automation while maintaining operational effectiveness, regulatory alignment, and long-term organizational trust.

DOI: http://doi.org/10.5281/zenodo.18326172

Published by: vikaspatanker