Advancements in Predictive Models for Software Defects: A Comprehensive Exploration
Authors:-Professor Mohamed Abdul Jailani, Kallal Bhakta

Abstract-This venture centers on foreseeing program bugs utilizing a dataset from the College of Geneva, Switzerland, which incorporates data from different program frameworks like Overshadow JDT Center, Overshadow PDE UI, and Lucene. By analyzing program properties such as lines of code, strategies, and traits, the point is to anticipate the number of bugs in progress. This foreknowledge makes a difference in proactive imperfection administration and chance relief. The venture envelops intensive information investigation, preprocessing, and visualization, taken after by progressed exploratory information investigation (EDA) utilizing machine learning and dimensionality lessening procedures. It addresses challenges like hyperparameter tuning and lesson awkwardness, endeavoring to classify computer program information by bug seriousness, from no bugs to different bugs. The extreme objective is to make strides in program support and streamline discharge forms.

DOI: 10.61137/ijsret.vol.10.issue4.186

Published by: Kajal Tripathi

Sewage Waste Water Treatment by the Hydrodynamic Cavitation Method
Authors:-Chanchal Valvi, Dr. Pankaj P. Gohil, Dr. Hemangi Desai

Abstract-The sewage water sample obtained after secondary treatment, was given treatment with Hydrodynamic Cavitation Method. Physico chemical parameters were determined using standard methods of APHA, before and after treatment at 24 hour in cavitation device. the water quality obtained is comparable to Drinking Water Standards (IS). The water quality parameters selected were: pH, Electrical Conductivity, Turbidity, TS,TSS, TDS, DO, Cl- ,Alkalinity (as CaCO3), Cu2+ ,Zn2+ ,Mg2+ Hardness, Total Hardness (as CaCO3), Phosphate and BOD. The highest reduction obtained was 88.88% for Cl- . Except TS, TSS and Cu2+ all the parameters were get back in the range of drinking water quality standards. The mechanism supports the reduction in parameter may be due to the collapse of cavities induces effects such as high shear forces, extreme temperatures, shock waves, turbulence, and extreme pressure in the fluid, formation of OHo free radicals provide to reduce pollution. The Cavitation method is proven to be the most effective over the other methods. Because, it does not require any chemical reagent, hence do not produce any hazardous chemical waste and maintain eco-friendly and economically sustainable environment benign technique for the treatment of wastewater.

DOI: 10.61137/ijsret.vol.10.issue3.185

Published by: Kajal Tripathi

Numerical Study of Flow Over NACA 2412 Airfoil at Various AOA’s
Authors:-Nadirge Chandravadan

Abstract-An aerodynamic study was conducted to examine the effect of airflow around the NACA 2412 airfoil using CFD methods. The airfoil’s coordinates were taken from the airfoil database and imported into a geometry modeler. A mesh was created, and simulations were performed using Fluid Flow (Fluent) software. The study involved solving the governing equations (Continuity, Reynolds Averaged Navier-Stokes, and Energy Equation) in 2-D using Fluent. Graphs were made to compare lift (CL) and drag (CD) coefficients at different angles of attack (α). Results showed that lift and drag forces increased with the angle of attack until reaching the stall point. The optimal angle of attack was found to be 8 degrees, where the NACA 2412 airfoil produced the highest lift-to- drag ratio. The critical stall angle was 16 degrees. Beyond this angle, the lift force decreased, indicating stall. The CFD simulation results closely matched the experimental results, indicating that CFD is a reliable alternative for determining drag and lift.

DOI: 10.61137/ijsret.vol.10.issue3.184

Published by: Kajal Tripathi

Hardware Implementation of BI- Directional Buck Boost Converter for V2g System with Hybrid Energy Storage System
Authors:-Scholar Samyuktha. T, Professor Ganesan.S

Abstract-In modern power system operations, demand side integration is one of the key functions which enables active consumer participation. Electric vehicles (EVs) encourage active participation of consumers for power management. In vehicle to grid integration (V2G), energy storage system (ESS) is connected with the grid through bidirectional converters. The topology for V2G integration consists of ESS, switching bidirectional buck-boost converter, full bridge inverter, and grid. Now-a-days, hybrid energy storage system (HESS) is an attractive solution for EVs. In this work, a topology for V2G with HESS is proposed. This topology comprises of an active HESS in which Li-ion battery is connected to the super capacitor via a bidirectional dc-dc half bridge converter, and full bridge inverter. The fuzzy logic controller using triangular membership functions and hysteresis current controller are proposed for inverters and bi-directional dc-dc converter respectively. The simulation of proposed topology is developed in MATLAB 2021 and the performance is verified. The hardware has been developed which comprises of a bi-directional buck-boost converter (HESS) and converter. The converter plays a crucial role in managing the bi-directional flow of energy between (EV) and the power grid, facilitating both charging and discharging operations. the several critical observations were made. The selected MOSFETs performed reliably under high-speed switching conditions, and the low inductors and capacitors minimized power losses. The tapping transformer provided robust electrical isolation and effective signal transfer, with adjustable voltage taps enhancing MOSFET switching performance. The DSP30F2010 microcontroller, using fuzzy logic control, offered precise and adaptive regulation.

DOI: 10.61137/ijsret.vol.10.issue4.183

Published by: Kajal Tripathi

Microplastic Menace: Unraveling the Presence, Sources and Health Impact in Domestic Tap Water
Authors:-Jyoti Punia

Abstract-Microplastics, tiny plastic particles less than five millimetres, are a significant ecological risk. They are found in soil, sediment, and surface water. A study examining microplastic contaminants in tap water in residential areas found three types: cellophane, cellulose, and poly (2, 2, 2-trifluoromethyl vinyl ether). The study highlights the need for effective mitigation measures and provides insights into the health concerns associated with different types and concentrations of microplastics. Ensuring safe and clean water is crucial for public health, making water quality protection essential for managing microplastic pollution.

DOI: 10.61137/ijsret.vol.10.issue4.182

Published by: Kajal Tripathi

Cost-Benefit Analysis of Open-Source VS. Commercial Test Automation Frameworks in Large-Scale Enterprise Applications
Authors:-Kodanda Rami Reddy Manukonda

Abstract-The abstract examines, in the context of large-scale enterprise applications, the cost-benefit comparison between commercial and open-source test automation frameworks. It compares the initial and continuing expenses of the two solutions before moving into the financial ramifications. Although open-source frameworks frequently have cheaper upfront costs, the analysis draws attention to potential hidden costs such the requirement for specialized knowledge, longer setup times, and ongoing maintenance. On the other hand, commercial frameworks usually come with hefty licensing costs, but they also provide excellent customer service, seamless integration, and improved capabilities that help hasten the testing procedure. In addition, the assessment takes into account community support, scalability, security, and long-term viability, giving a thorough picture of the effects different frameworks have on total cost of ownership, productivity, and risk management. The results indicate that although open-source solutions might be beneficial for smaller projects or companies with strong internal expertise, commercial frameworks typically offer larger businesses better value because of their dependability, user-friendliness, and extensive support, which eventually results in more predictable outcomes and reduced risk throughout the project lifecycle.

DOI: 10.61137/ijsret.vol.9.issue6.181

Published by: Kajal Tripathi

A Blockchain Based DevOPS for Cloud and Edge Computing in Risk Classification
Authors:Hemanth Swamy

Abstract- Overlying environments with large volumes of data are challenging to handle on a single server. Consequently, knowing how to secure unpredictable data in a changing setting is crucial. The authors express worry about the potential security risks associated with susceptible data in a distributive system based on the mobile edge. Therefore, it would seem that edge computing is a great vantage point from which to conduct training in an ecosystem based on the edge. Data security, exposure of data, and the likelihood of a data breach may all be enhanced by combining machine learning methods with blockchain’s consensus methodology and edge computing. In this study, we demonstrate how to integrate realistic ML approaches into a DevOps environment. Our system’s danger assessment is a machine learning model that estimates the risk level of each authentication attempt based on digital identity variables like IP address, browser user agent, and user behavior. Using a subset of login data variables, we validated our system and built risk classifier models to determine the amount of danger posed by users. Therefore, a way to train the shared data is via the idea of machine learning. Under the watchful eye of two-factor authentication, data security was previewed in a dataset that included several exposed, vulnerable, recovered, and protected pieces of information. Data and security vulnerabilities in smart computing edge devices, as well as their fixes, are covered in this study. Machine learning methods, including various classifiers and optimization algorithms, plus the blockchain consensus approach, provide data confidentiality in the suggested model. In addition, the authors used an edge computing setting to implement the suggested techniques by sending data in several batches to various customers. Consequently, the use of blockchain servers ensured that client anonymity was preserved. In addition, the writers used the federated learning method to train separate batches of client data. This study presents the outcomes of a training model that utilizes blockchain technology in an edge-based technology setting.

DOI: 10.61137/ijsret.vol.10.issue1.180

Published by: Kajal Tripathi

On Superconductivity, Dimensionality, and Destructive Interference: The Destructive Interference Theory of Superconductivity
Authors:-Donald J. Dodd

Abstract-The “Destructive Interference Theory of Super conductivity” is based on a hypothetical relationship between the destructive interference of phonons and the effect lower energy density has on dimensionality. This lower energy density and subsequent high number of dimensions with open apertures, higher dimensionality, allows the quantum entanglement of electrons. The hypothesis is predicated on a second hypothesis, the “Theory of Dimensionality,” describing, what Einstein characterized as a 4-dimensional spacetime fabric, as a highly dimensional sub-plank-sized quantum particle. At quantum mechanical scales, energy manifests itself as discrete packets of energy called quanta, and it should be apparent that Einstein’s spacetime fabric is no exception. Effects such as wormholes, tunneling, and quantum entanglement are confined to a highly dimensional quantum mechanical world because, at higher energy densities, in joules per meter cubed (J/m3), well below higher energy density found at room temperature, the normally open apertures of the dimensions that allow these effects, are closed. [26] The innate spring tension that holds the apertures of the many dimensions open, and allows energy to pass through them, will close in sequence from the highest dimension to the lowest as energy density increases, like a force compressing a spring. Phonon destructive interference, occurring when two matter waves of the same amplitude in opposite directions come together and cancel each other out, plays a critical role in the formation of lower energy density regions within a solid. [25] A phonon is a bosonic particle with vibration frequencies that typically range from 10 to 30 THz with an amplitude from 0.03 to 0.08 angstroms. [17] This wave-like virtual particle exhibits properties that include constructive and destructive interference, similar to the light and dark regions of the well-known double slit experiment. There is an inverse relationship between highly dimensional spacetime, referred to here as dimensionality, and the lower energy density regions caused within matter caused by the destructive interference. Spacetime is composed of highly elastic, highly dimensional, sub-plank-sized particles, whose size or dimensionality, the number of dimensions with open apertures, is inversely related to their local energy density. In other words, the open apertures of a spacetime particle, close in sequence, like a cascade, from the highest to the lowest dimension as energy density increases to its extrema – a mass approaching the speed of light. Superconductivity is one of many higher-dimensional effects of dimensionality. It occurs at and below a specific energy density when the aperture of the dimension that allows the quantum entanglement of electrons is open. Factors such as temperature and destructive interference are critical in achieving that critical energy density.

DOI: 10.61137/ijsret.vol.10.issue4.179

Published by: Kajal Tripathi

Synergizing Deep Learning and IoT: A Tri-Module Approach for Intelligent Home Security
Authors:-Likhith Sai Valluru, Parnashri Nandam, Professor Dr. Y. Rama Devi, Assistant Professor G. Kavita

Abstract-In our current digital phase, ensuring security and safety is paramount, especially when it comes to protecting our homes. Traditional methods, like relying on keys, pose vulnerabilities that can result in oversights and potential security ruptures. A robust home security system is necessary for addressing these concerns. Historically, people have secured their homes with keys, but the risk of theft increases when residents forget to lock their doors. To tackle this challenge, the research at hand leverages Deep Learning and Internet of Things (IoT) technology to elevate home security. The proposed system introduces a door lock mechanism based on facial recognition to ensure that only authorized individuals, such as friends and family, can access the premises, thereby deterring intruders. This forward-thinking solution goes beyond homes, extending its application to workplaces and campuses. Utilizing facial recognition as a seamless means of unlocking doors eliminates the need for physical effort. The system incorporates biometric and two-factor authentication, enhancing security with the integration of OpenCV. This concept combines biometric matching, human face recognition, and Twilio service-powered One-Time Password (OTP) transmission. It is powered by a Raspberry Pi 4 microprocessor. Although face recognition-based door locking systems have been around for a while, this research stands out since it incorporates extra security elements while still being reasonably priced. Consequently, it presents a comprehensive solution for heightened security in various settings.

DOI: 10.61137/ijsret.vol.10.issue3.178

Published by: Kajal Tripathi

Harnessing the Power of Gen AI & Cloud Computing for Customer Relationship Management
Authors:-Rohit Alladi

Abstract-With rapid technological transformation and dynamic digital landscape partnership of Generative AI (Gen AI) & cloud computing is revolutionizing customer engagement strategies and driving innovations. Gen AI combined with Cloud computing presents unprecedented opportunities for businesses to forge deeper engagement with customers and gain loyalty. In today’s highly competitive business landscape it’s imperative for every business to stay ahead of the curve and address the challenges to avoid churn and focus on driving business growth. These challenges require deployment of the right mix of technologies. Gen AI provides a very powerful mechanism to extend tailor approach to interaction and service provision. while cloud computing offers a scalable, flexible and economic infrastructure for deploying AI powered solutions to meet evolving customer expectations. Having the right combination of Gen AI and Cloud computing enables customer relationship management applications to process vast amounts of data in real-time, empowering businesses towards actionable insights & delivering targeted & hyper personal experiences to the customers.

DOI: 10.61137/ijsret.vol.10.issue3.177

Published by: Kajal Tripathi