Volume 12 Issue 3

A Review on Effects of Different Nanofluids on Trapezoidal Corrugated Channel

Authors- M.Tech Scholar Abhishek Ramteke, Professor Dr. Sanjay Kumar Singh

Abstract- Heating/cooling processes using different techniques are essential in many industrial applications such as production and electronics processes, and consequently, all machines require reducing or increasing heat transfer. Despite the high pressure drop caused by turbulent flow in complicated channels, the use of corrugation in heat exchangers has received a lot of attention during the last two decades. Therefore, corrugated surface technique is the promising method to intensify the thermal performance and compactness of heat transfer instruments in some cooling system applications, especially in compact plate heat exchangers. Corrugated walls depend on manipulating the fluid direction of the main flow, which helps induce recirculation flow vortexes that enhance heat transfer. On the other hand, the use of traditional fluids in this technique has been limited due to their somewhat lackluster thermal properties. Therefore, the poor thermophysical properties of these liquids are considered as the major obstacle to improving heat transfer processes. The introduction of nanoparticles into conventional liquids offers a viable solution to improving the thermal properties of these liquids.

AI Assisted Tele-Medicine KIOSK

Authors- Associate Professor Dr Nandini S, Anusha k, Chethana D P, Ganasudha G K, Lavanya T

Abstract- The growing prevalence of chronic diseases has resulted in a heightened need for primary healthcare services in numerous industrialized nations. Modern healthcare technology tools have the potential to address the shortage of primary care providers. In this study we discuss the creation and implementation of an automated healthcare kiosk in a primary care setting for managing patients with stable chronic conditions. One hundred individuals with stable chronic illnesses were enlisted from a primary care clinic and utilized the kiosk instead of traditional doctor appointments for two consecutive follow-up visits. Both patients and physicians expressed contentment with the usage of the kiosk with positive feedback in all areas. However the independent utilization of the kiosk was dependent on the patient’s proficiency in language and level of education. The use of healthcare kiosks presents an alternative approach to managing stable chronic diseases potentially replacing the need for physician consultations and enhancing access to primary healthcare. Patients including those with limited literacy and education welcomed the use of these innovative healthcare technology tools. Prior to implementing kiosk-based technology in healthcare settings certain factors such as environment and patient needs should be optimized. Despite recent advancements in healthcare providing adequate medical services in rural India remains a persistent challenge that requires innovative solutions. To bridge this gap an AI-assisted telemedicine robotic kiosk can be set up in any village providing easy access to expert doctors based on the individual’s medical condition. Users can authenticate their identity through a biometric scanner followed by a consultation with a robot that inquires about their illness. The individual is then directed to an expert doctor via an e-sanjeevani app. Following the consultation necessary medication and services can be provided through a local Asha worker without any delay.

Innovation Takes Flight: Hanessing the Power of Drones for Progress

Authors- Aditi Rai, Ayushya Tripathi, Aparna Gupta, Ashutosh Pandey, Professor Dr. Soni Changlani

Abstract- The article provides an in-depth exploration of drones, focusing on their construction, key components, and rising popularity. Drones, also known as unmanned aerial vehicles (UAVs), have become increasingly prevalent due to their affordability and diverse applications. One of the notable features of drones is their unmanned nature, meaning they can operate without a pilot onboard. However, despite their advantages, drones carry certain risks, such as accidents caused by battery failure, adverse weather conditions, or collisions with obstacles like trees or buildings. The versatility of drones extends beyond recreational and military applications, finding utility in fields like agriculture, cinematography, and surveillance. Since the beginning of 2013, many people have started flying drones just for fun. The widespread availability and ease of use of drones are expected to lead to their increased use in various sectors, from recreational activities to commercial endeavors.

Banking 4.0: Recent Trends of Digitalization in the Present World

Authors- Assistant Professor Dr. Chandrashekhar R, Assistant Professor Dr. Tejashwini K C

Abstract- Customer preferences and expectations have changed as a result of the banking industry’s use of digital technology. The primary goal of the study is to understand how digitization have affected e-banking services. The relationship between the bank and its customers has typically been one-to-one. Curiously, the Indian government has been taking numerous actions to introduce technological developments in the country’s banking industry. The consumer response has been extremely positive to the introduction of debit cards, credit cards, NEFT, RTGS, Jan Dhan Yojana, White label ATMs, Mobile banking, Internet banking, and many other significant initiatives to improve banking in India. These varied digital products assist the businesses (service providers) in enhancing their company performance and maintaining market competitiveness. In order to boost their profitability, strengthen their financial position, and enhance performance, they also help to increase market share. They all point out that despite the recent ten years of significant technical improvement in Department of Financial Services (DFS), the element influencing the firm’s performance and profitability in academic literature has not received the appropriate attention. A growing number of people are using and accessing the financial services offered by banks thanks to developing new technologies like app banking and mobile wallets.

A Study on Painters Perception and their Level of Satisfaction with Special Reference to Construction Chemicals of Berger Paints India Ltd-Kottayam Division

Authors- Alen Ipe Shajan, Assistant Professor Dr.K.Sankar Singh

Abstract- This study focuses on examining the perception of painters and their level of satisfaction with construction chemicals offered by Berger Paints India Ltd in the Kottayam division. Construction chemicals play a vital role in enhancing the durability and performance of paints, there by influencing the overall satisfaction of painters and customers. The objectives of the study aim to investigate the factors that shape the perception of painters towards construction chemicals and the extent to which these products meet their expectations. Additionally, the study aims to identify dissatisfaction or improvement opportunities regarding the construction chemicals provided by Berger Paints India Ltd. The research outcomes can be utilized by Berger Paints India Ltd to enhance their product offerings and tailor them to better meet the needs and expectations of painters. Overall, this study seeks to shed light on the perception and level of satisfaction of painters regarding construction chemicals offered by Berger Paints India Ltd in the Kottayam division, to improve the company’s products and services, as well as enhance the overall customer experience.

Driver Drowsiness Detection System

Authors- Aishwarya Patil, Vaishnavi Baheti, Vaishnavi Patil, Pratiksha Giribuva, Rasika Kachore, Archana Jadhav

Abstract- Drowsy driving poses a significant risk to road safety, leading to accidents with potentially severe consequences. To address this issue, we propose a driver drowsiness detection system utilizing yawning as a prominent indicator of driver fatigue. Yawning is a physiological response closely associated with drowsiness and can serve as a reliable marker for assessing driver alertness levels. Our system employs facial recognition and machine learning algorithms to detect and analyze yawning instances captured by vehicle-mounted cameras. Features such as yawning duration, frequency, and intensity are extracted and fed into a classification model trained to distinguish between normal behavior and signs of drowsiness. The detection of yawning is efficient and works under different situations. This project describes on how to detect the mouth in a video recorded from the. Within the video, the member will drive the driving reenactment framework and a camera will be setup in front of the driver. The video will be recorded using the webcam to record the moves of the driver. The image-processing model will detect the are of mouth and then capture the yawning from the frames generated from the video. The facial analysis is popular research areas these days, which is used for face recognition, tracking human for security, etc. This project is focused on the localization of mouth, which involves looking at the entire image of the face, and determining the position of mouth, by applying the existing methods in image- processing algorithm. Once the position of the mouth is located, the system is designed to determine whether the mouth is opened or closed, and detect fatigue and drowsiness.

Automated Gesture Controlled Presentation

Authors- Assistant professor Aakanksha S Choubey, B. Harshita, Himanshi Sahu, Jhalak Sahu, Priyali Pandey

Abstract- The objective of this research paper is to construct a presentation controller which uses hand gestures as the system’s input to control presentation. The OpenCV module is mostly utilized in this implementation to control the gestures. This system primarily employs a web camera to record or capture photos and videos, it allows real time recognition of hand gestures captured from webcam and translates them into actionable commands. This project is very helpful in a situation where the users cannot use any kinds of input devices or touch them, With the help of gesture recognition one can easily a specific action needed without physically access the input methods for example mouse, keypad etc. This research has used Machine Learning to detect gestures with subtle differences and tried to map them with some fundamental PowerPoint slideshow controlling functions using Python.

Estimation of Transport Properties of Polar Solvents from 298.15-318.15K

Authors- Naveen Awasthi, Jyoti Bhadauria, Divya Jyoti Mishra, Nalini Dwivedi

Abstract- In this paper, we have computed the viscosity of a solution containing to polar solvents such as benzyl alcohol and 2-propanol from Jouyban Acree (JA) model based on least square regression analysis method and McAllister multi body interaction model based on Eyring’s theory absolute reaction rate from 298.15-318.15K. Results obtained from were compared with the literature value. Standard deviation was the criterion of the success of results. Jouyban Acree (JA) model found to be more consistent with experimental findings.

A Survey of Software Defect Prediction Using Machine Learning Algorithms

Authors- Research Scholar Mr. Raja Lodhi, Assistant Professor Rajkumar Sharma

Abstract- Software Defect Prediction [SDP] plays an important role in the active research areas of software engineering. A software defect is an error, bug, flaw, fault, malfunction or mistake in software that causes it to create a wrong or unexpected outcome. The major risk factors related with a software defect which is not detected during the early phase of software development are time, quality, cost, effort and wastage of resources. Defects may occur in any phase of software development. Booming software companies focus concentration on software quality, particularly during the early phase of the software development .Thus the key objective of any organization is to determine and correct the defects in an early phase of Software Development Life Cycle [SDLC]. To improve the quality of software, data mining techniques have been applied to build predictions regarding the failure of software components by exploiting past data of software components and their defects. This paper reviewed the state of art in the field of software defect management and prediction, and offered data mining techniques in brief.

Enhancing Satellite Image Classification with CNN

Authors- P Rakesh Vardhan, G Srujan Sharma, T Shiva Shankar, Associate Professor Mr. P. Raveendra Babu

Abstract- There exist several applications for satellite images, such as environmental monitoring, law enforcement, and disaster response. For these applications, manual identification within such imagery is essential. Automation is necessary, though, because of the large geographic areas and scarcity of human resources for analysis. For such jobs, traditional object recognition algorithms frequently suffer from poor accuracy and dependability. CNN in particular, are part of deep learning and have shown promise in automating image interpretation tasks. In this study,. In particular, we offer a deep learning method that is intended to categorize dataset items and facilities into 60 distinct types. Our system comprises an ensemble of CNNs augmented Using additional neural networks that combine visual characteristics with satellite information. Python is used for implementation, and the deep learning libraries Keras and Tensor Flow are utilised. attaining an F1 score of 0.797 and an overall accuracy of 83%.

React JS: A Open Source Modern Web Development Java Script Library for Front-end Development

Authors- Scholar Umesh Agarwal, Professor Dr. Vishal Shrivastava, Assistant Professor Dr. Akhil Pandey

Abstract- React, also known as React.js, is a highly popular open-source JavaScript library used for building user interfaces in single-page applications and mobile app development. It’s favored for its speed, simplicity, and scalability, offering features like JSX, stateful components, and a virtual Document Object Model (Virtual DOM). JSX is optional but aids in providing helpful error messages. Companies like Facebook and Instagram use React for large and complex online applications, enabling data updates without page refreshes for fast and robust web apps. React is versatile, supporting both simple and complex applications and can be used in the browser and on the server with Node.js. Why choose React over other front-end technologies? React offers a reliable choice with a vibrant community of over 1,400 developers and more than 92,000 websites. Its advantages include a smart diffing algorithm for efficient DOM updates, reusable components for easy app development, and a non-prescriptive approach, allowing a rich library selection. React’s lifecycle methods and React Hooks provide a powerful way to manage component events throughout their lifecycle.

Accident Prediction System Using Decision Tree Algorithm

Authors- Okoh Kate Imanyi, Agaji Iorshase

Abstract- Road accidents cause enormous human and financial losses all around the world. This research presents an Accident Prediction System (APS) that predicts the probability of traffic accidents by applying the Decision Trees algorithm. To build decision trees for prediction, the APS incorporates weather, traffic patterns, road infrastructure, and past accident data. A dataset containing numerous accident-related characteristics, such as location, vehicle speed, road type, time of day, and environmental factors, is used to train the system by applying the decision trees algorithm. Performance evaluation of this system shows promising accuracy in accident prediction through rigorous evaluation and validation processes. In addition to identifying high-risk locations that are prone to accidents, the APS also helps develop preventative strategies for traffic control and accident avoidance. By giving stakeholders, such as traffic authorities, urban planners, and law enforcement agencies, a trustworthy forecasting tool to lessen the frequency and severity of traffic incidents, this research helps to improve road safety.

Streamlining Academic Writing: A Descriptive Analysis of Markdown to LaTeX Convertibility in Typesetting Software

Authors- Snehit Sah, Madhavi Dixit

Abstract- Typesetting software has undergone significant evolution over the years, with LaTeX emerging as the standard for academic writing due to its powerful formatting capabilities. However, the rise of Markdown as a more user-friendly alternative has sparked discussions on the ease of use and convertibility of Markdown to LaTeX. This essay will delve into a descriptive analysis of Markdown to LaTeX convertibility in typesetting software, exploring the advantages of Markdown in academic writing, the challenges faced in converting Markdown to LaTeX, and the overall implications for streamlining academic writing processes. This paper intends to connect the distinct capabilities of file formatting and code execution at a common point. It presents a comprehensive solution for technical papers that includes considerable code execution as well as the responsibility of generating the desired outcome. Such technical files also necessitate a template for optimal display, which necessitates manual labor. The proposed web application provides a user-interactive interface for completing technically complex activities using clearly understandable predefined templates for various domains or templates involving file execution into a portable document format. Ephemeral docker containers are utilised for pandoc to render laTeX conversions for maintaining the nature of complexity involved while writing academic documents.

Voice Controlled Wireless Electronic Notice Board Using Android

Authors- Vinita Barthwal, Gourav Baboria, Sameer Kumar, Yash Aryan

Abstract- Notice Board is primary thing in any institution / organization or public utility places like bus stations, railway stations and parks. But sticking various notices day-to-day is quite a difficult process. A separate person is required to take care of this notices display. This project deals about an advanced hi-tech wireless notice board. The main objective of the project is to develop a wireless notice board that displays notices when a message is sent from the users mobile. While the user sends the message from the mobile, the remote operation is achieved by any smart-phone/Tablet etc., with Android OS, upon a GUI (Graphical User Interface) based voice operation. Transmitting end uses an Android application device remote through which commands are transmitted. At the receiver end, these commands are converted to texts used which are displayed on a 16X2 LCD – interfaced to the microcontroller. Serial communication data sent from the Android application is received by a Bluetooth receiver interfaced to the microcontroller. The program on the microcontroller refers to the serial data to display the received data on 16X2 LCD. The power supply consists of a step-down transformer 230/12V, which steps down the voltage to 12V AC. This is converted to DC using a Bridge rectifier. The ripples are removed using a capacitive filter and it is then regulated to +5V using a voltage regulator 7805, which is required or the operation of the microcontroller and other components.

Credit Card Fraud Detection Using Decision Tree Algorithm

Authors- Poornima Mishra, Pranjal Dewangan, Sagar Dewangan, Sharmin Ansari, Assistant Professor Abhishek Kumar Dewangan

Abstract- Credit card fraud poses significant challenges to financial institutions, merchants, and consumers alike. As fraudulent activities continue to evolve in sophistication and frequency, the need for robust fraud detection mechanisms becomes imperative. In this study, we propose the utilization of the Decision Tree algorithm as an effective tool for detecting credit card fraud. Decision trees are widely recognized for their simplicity, interpretability, and ability to handle both numerical and categorical data effectively. Leveraging these advantages, we employ a Decision Tree model to analyze historical credit card transaction data, identifying patterns and anomalies indicative of fraudulent behavior.

Emotion Classification

Authors- Aaditya Sinha, Ankit Kumar, Ankit Bisht, Akshat Chaudhary

Abstract- EmoNet, a social media platform known for its user-friendly interface and innovative features, has emerged as a prominent space for authentic self-expression, meaningful conversations, and global connection. This rapid growth has fostered a dynamic digital ecosystem where diverse communities collaborate and create. However, emotions play a critical role in social media interactions, influencing user behavior, content engagement, and community dynamics. This paper highlights the significance of emotion classification in social media. By accurately analyzing user-generated content, platforms like EmoNet can gain valuable insights into user engagement, predict trends, and personalize content recommendations. Ultimately, emotion classification empowers social media platforms to cultivate a more empathetic and inclusive online environment.

Advancements in Cloud Data Handling and Automation

Authors- Assistant Professor Dr.B.M.Gayathri, Assistant Professor R.Rajeswari

Abstract- This paper info the diverse services of Amazon Web Services a extensive set of cloud-primarily based totally merchandise together with compute, storage, databases, analytics, networking, mobile, developer tools, control tools, IoT, security, and corporation applications: on-demand, to be had in seconds, with pay-as-you-move pricing. From statistics warehousing to deployment tools, directories to content material delivery, over two hundred AWS offerings are to be had. New offerings may be provisioned quick, without the in advance capital expense. This permits enterprises, start-ups, small and medium-sized businesses, and clients with inside the public quarter to get admission to the constructing blocks they want to reply quick to converting enterprise requirements. This whitepaper gives you with an outline of the blessings of the AWS Cloud and introduces you to the offerings that make up the platform.

Track Break Detection: Protecting One of the Largest Means of Transport from Catastrophe

Authors- Gargie Tiwari, Apurva Tomar, Arunima Singh Parihar, Aditya Narayan, Professor Dr.Monika Kapoor

Abstract- Rail transportation is a cornerstone of India’s infrastructure, boasting one of the world’s largest railway networks. Despite its growth, the Indian rail system grapples with persistent challenges such as unsafe crossings, fire hazards, and unmonitored track conditions leading to accidents and derailments. Seasonal fluctuations cause tracks to expand and contract, potentially resulting in track cracks. To address these issues, a proposed system employs sensors to detect and track obstacles and cracks, sending alerts to control rooms via SMS using GSM and GPS modules. Railway transportation is pivotal for global mobility and logistics. Consequently, the development of advanced track brake systems is imperative. Traditional braking systems suffer from friction-related issues, including wear, heat, and reduced performance in adverse weather. Advanced track brake systems leverage innovative technologies and materials to overcome these challenges. In conclusion, the adoption of advanced track brake systems signifies a significant advancement in enhancing railway safety, efficiency, and sustainability. Incorporating electromagnetic and regenerative braking, sensor technologies, and adaptive algorithms, these systems offer a comprehensive solution to meet the evolving demands of modern railways. Continued research and investment are vital for further improving railway safety and performance worldwide.

The Supremacy of Inflation Accounting

Authors- Sarah Nabeel Polus, Mr. Avinash Bondu

Abstract- A considerable number of countries in the world are prone to inflation either with a big or small percentage. This has become constant as there are many external and internal factors behind the causation. Economies of the world try various techniques and implement various policies, to restrict inflation. However, the amount of inflation can be decreased but a complete eradication of inflation seemed to be impossible. Since the inflation results in the price and value changes on the assets or products, there has been a need raised to be considered in the accounting era for the reporting of financial statements. Standards by various international and national accounting bodies were issued to deal with the accounting for inflation. The present study analyzes the importance of inflation accounting by evaluating its role and impact of financial statements. Financial statements from a company of hyperinflationary economy (Celulosa Argentina company from Argentina) are considered and forecasted, variations will be determined using MS Excel and statistical techniques are implied and interpretations were drawn. The study concludes that the impact of inflation rate in high on various components of financial statements in hyper inflationary economy and it was less on that of a normal economy.

DOI: /10.61463/ijset.vol.12.issue3.174

International Transfer Pricing: Privileges and Detriments

Authors- Maryam Salwan Sabri, Mr. Avinash Bondu

Abstract- Transfer pricing has been representing a key position in the contemporary accounting world, that facilitates the Multinational corporates, to lower the burden of tax by transferring their products to the subsidiary nations or vice versa, to get the advantage of tax benefit with increased or decreased costs of sales. Multiple scenarios have been registered tracing out the implementation of transfer pricing by the companies to deceive the governments by paying less taxes. This research considers the transfer pricing policies of a parent company with its respective subsidiaries and the corresponding tax rates, and provide numerical evidence of how the transfer pricing is benefiting both parties, the MNC and the governments. Forecast of the financial statements for four years of Apple company are made by dividing the proportion of production of the company in two countries and the results exhibit a substantial margin for the companies implementing transfer pricing policies. Governments of the corresponding parties experienced a lot of difference in the tax revenue as well. Suggestions are provided that legal compliance by the organizations are required to balance the benefits for both the parties and the society.

DOI: /10.61463/ijset.vol.12.issue3.175

A Comprehensive Analysis of Parallel Heat Pipe System with Evolution of its Properties

Authors- Nikhlesh Pindoliya, Professor Khemraj Beragi

Abstract- Genetic Algorithm (GA) based heat exchanger analysis employs evolutionary optimization techniques to enhance the performance and efficiency of heat exchangers. By mimicking natural selection processes, GA iteratively searches for optimal design parameters such as geometry, material properties, and flow configurations. This method efficiently navigates the complex solution space, identifying designs that maximize heat transfer and minimize costs. GA’s flexibility and robustness make it an effective tool for tackling the multifaceted challenges in heat exchanger design, leading to improved thermal performance and economic benefits.

Web Based Surveillance Robot

Authors- Hardik Arora, Harshika Patidar, Jai Gupta, Melisa Sherin Philip, Professor Dr. Soni Changlani

Abstract- This venture presents an inventive web-controlled camera framework fueled by Arduino, offering savvy remote checking and control. Utilizing the Arduino’s capabilities and connectivity, the framework empowers ongoing video catch and transmission. It’s easy-to-understand web interface works with remote access, giving live video feeds and dynamic container, slant, and zoom (PTZ) controls for flexible camera direction changes. Security is a foremost worry, with the execution of hearty validation and encryption conventions guaranteeing information protection and restricting admittance to approved clients, in this way relieving unapproved interruption gambles. The framework’s adaptability is shown through its versatility, making it versatile to different conditions like home security and modern reconnaissance. Mix of numerous cameras upgrades inclusion, framing a far-reaching reconnaissance network fit for observing broad regions. Furthermore, movement recognition calculations upgrade productivity by instantly making clients aware of strange exercises, empowering proactive danger reactions. This venture represents a reasonable and adaptable arrangement with viable applications. By giving experiences into the developing scene of remote observing and control in observation innovation, it adds to the progression of safety frameworks. The framework’s expense adequacy and adaptability make it appropriate for different settings, from private homes to modern offices. Overall, this endeavor showcases the potential of harnessing innovative technology like Arduino to address contemporary surveillance challenges and meet the demands of modern security needs.

Machine Learning-Based Sales Forecasting and Inventory Optimization

Authors- Associate Professor Rashmi Amardeep, Prakhar Anant, Priya B Gunali, Riya Raikar, S Deepak Dhore Reddy

Abstract- This project introduces a novel approach to sales prediction utilizing machine learning algorithms, aiming to revolutionize sales forecasting and enhance business decision-making processes. By leveraging advanced machine learning techniques, the project analyzes historical sales data to predict future sales trends accurately. The methodology involves the implementation of three prominent machine learning algorithms—Long Short-Term Memory, ARIMA and XG Boost to identify patterns and correlations within the dataset. Key features such as temporal factors, promotional activities, and market dynamics are integrated into the analysis to capture the intricacies of sales behavior the system offers an intuitive interface for entering fresh data and generating sales predictions in real time. Performance metrics assessment underscores the effectiveness of each algorithm in precisely forecasting sales figures. The project’s predictive analytics capabilities empower businesses to optimize inventory management, devise targeted marketing strategies, and allocate resources effectively. By leveraging the capabilities of machine learning, companies can acquire valuable insights into consumer behavior and market trends. This empowers proactive decision-making and fosters sustainable growth within the competitive business environment.

Deep Fake Detection Using CNN

Authors- Sudip Ghosh, Saikat Dey

Abstract- This study introduces a deep learning approach for predicting Deep fakes using Convolutional Neural Networks (CNNs). The methodology entails training a CNN model on a dataset comprising both authentic and manipulated images sourced from Kaggle. Subsequently, transfer learning is applied by leveraging the pre-trained Xception model, which has been trained on the extensive Image Net dataset. Through this process, the model learns to differentiate between real and fake images by discerning unique patterns and features inherent to each category. Preliminary results indicate that the proposed CNN-based approach demonstrates satisfactory performance in identifying fake images. Efforts are ongoing to further enhance the accuracy of the model with the aim of achieving even better results.

Exploring Contrastive Analysis for Energy Prediction in Cloud Data Centers: A Regressive Approach

Authors- Dr. M.V. Vijaya Saradhi, Poonam Sharma, Thaduri Akanksha, Madhiraju Purnima, Thungapati Sai Kumar

Abstract- Data centers play a pivotal role in modern Internet and cloud computing systems, yet their escalating energy needs present formidable hurdles. Precise energy consumption forecasts are indispensable for optimizing resource allocation. Despite numerous methods proposed, a gap persists in rigorously tackling this issue. Existing approaches often falter in capturing the intricate and stochastic energy consumption patterns, necessitating more comprehensive methodologies. The suggested approach pioneers a novel method for predicting energy usage in cloud data centers, emphasizing the incorporation of random uncertainty. Recognizing this uncertainty is vital due to the variability inherent in factors impacting energy consumption, such as workload fluctuations and hardware failures. By employing regression distributions to model random uncertainty, the methodology aims to more effectively encapsulate the statistical characteristics of energy consumption compared to conventional deterministic models. Rather than furnishing deterministic forecasts, the methodology conceptualizes energy consumption predictions as random variables drawn from regression-derived distributions. This probabilistic paradigm acknowledges and quantifies the inherent uncertainty in energy consumption predictions. Moreover, it extends beyond individual data centers, providing probabilistic forecasts for diverse data center portfolios, accommodating varied configurations and workloads. The methodology introduces several pivotal methodological innovations to enhance prediction accuracy. It proposes a naive multiple linear regression model as a baseline for capturing fundamental relationships. Additionally, it presents a pioneering approach that combines quantile regression and empirical copulas to estimate joint distributions of random variables, capturing complex interdependencies among energy consumption variables. Finally, a weighted correction method, grounded in constrained quantile regression, is introduced to refine predictive distributions, further bolstering accuracy. In conclusion, the methodology addresses the critical challenge of energy consumption prediction in data c\e\nters by embracing the stochastic nature of energy usage. Through rigorous statistical modeling and innovative techniques, it represents a substantial advancement, fostering a nuanced comprehension of energy consumption dynamics and facilitating informed and efficient management strategies.

Developing an End-to-End Secure Chat Application

Authors- Vaibhav, Bhaskar Chauhan

Abstract- Chat applications have emerged as indispensable tools on smartphones, offering users the ability to exchange text messages, images, and files at no cost. However, ensuring the security of these communications is paramount. This paper proposes a secure chat application that implements End-to-End encryption, safeguarding private information exchanged between users and providing robust data protection. The application also addresses storage security concerns. By outlining a set of requirements for a secure chat application, this paper informs the design process. The proposed application is evaluated against these requirements and compared with existing popular alternatives to assess its security features. Furthermore, the application undergoes rigorous testing to validate its End-to-End security capabilities.

DOI: /10.61463/ijset.vol.12.issue3.176

AIVA: A Personalized AI Tutor

Authors- Aman V Shet, Bhargavi P, Prajwal M R, Assistant Professor Mrs. Divya M S

Abstract- AIVA, our AI tutor, tackles personalized learning for primary and high school students. Through initial questions, AIVA tailors a Large Language Model using relevant materials for each student’s grade level. This dynamic approach personalizes learning, fostering comprehension and a love for knowledge. AIVA complements educators, acting as a guide to make education accessible and engaging.

DOI: /10.61463/ijset.vol.12.issue3.295

Influence of Groove Angle on Pitting Corrosion Resistance, Mechanical, and Metallurgical Properties of Gas Tungsten Arc Welded AISI 304 Stainless Steel Joints

Authors- Research Scholar Gaurav Sharma, Assistant Professor Sahil Duggal

Abstract- This study aims to investigate the influence of groove angle on the welding process, pitting corrosion resistance, mechanical properties, and metallurgical characteristics of Gas Tungsten Arc Welded (GTAW) joints in 6mm thick AISI 304 stainless steel (SS) plates. Three different groove angles are employed in the welding process, and the resulting joints are subjected to comprehensive analysis. The research reveals significant findings regarding pitting corrosion resistance, impact toughness, ultimate tensile strength (UTS), heat dissipation characteristics, and hardness of the welded joints. Notably, joints with smaller groove angles exhibit superior pitting corrosion resistance, higher UTS, impact toughness, and hardness. Additionally, variations in groove angle lead to differences in heat dissipation characteristics across the joints. Based on these findings, recommendations are made to prioritize smaller groove angles for achieving better pitting resistance and mechanical properties in GTAW welded joints of AISI 304 SS. This study contributes valuable insights into optimizing welding processes and enhancing the performance of welded joints in stainless steel applications.

Study on a Particular Form of Cubic Equation

Authors- Arnab Gain

Abstract- In this paper the general form of cubic equation has been modified into a particular form and has been thoroughly studied. To evaluate exact roots of the modified form, a simplified formula has been derived and presented. This derived formula is similar to that of Sridharacharya’s formula for solving quadratic equation and the similarities has been pointed out in this paper. Furthermore this particular form behaves in a special manner when Cardan’s method is applied on it for finding the roots. In the preliminaries section basic definitions, rules for round off and the Cardan’s method for solving cubic equations have been stated in this paper for better understanding purposes. Apart from finding out the roots of the special types of cubic equation, the nature of the roots has also been discussed here. To illustrate utility of the derived formula appropriate examples have been provided. A brief historical background of evaluation of cubic equation is also given in the introduction section and names of various well known methods to solve the cubic equations are also mentioned here. This derived formula will be very helpful for solving the particular types of cubic equations discussed here. More over the derived formula is very easy to remember and recall in the time of need. Some interesting observations have been made throughout the paper. The similarity of the derived formula with that of Sridharacharya’s formula is matter of interest in the paper.

DOI: /10.61463/ijset.vol.12.issue3.177

Anti-Inflammatory Activities of Some Medicinal Plants

Authors- Shailendra Sisodiya, Rajesh Kumar Tengriya

Abstract- Inflammation is classically regarded as a feature of innate immunity. It is characterized by redness, swelling at the site of injury and pain due to the influx of neutrophils, leukocytes and quickly followed by the influx of monocytes. Monocytes mature to inflammatory macrophages, proliferate and eventually alter the cellular function. The initiation and rapid onset of inflammation is mediated through receptors, unlike in adaptive immunity and involves 4 stages- a trigger by the stimulant (sterile/ infection), a radar that recognises the danger (receptors), signal transduction to the nucleus to initiate production of various mediators for combating the damage and clearance of the stimuli. The inflammatory response is the coordinate activation of signalling pathways that regulate inflammatory mediator levels in resident tissue cells and inflammatory cells recruited from the blood. Inflammation is a common pathogenesis of many chronic diseases, including cardiovascular and bowel diseases, diabetes, arthritis, and cancer (Lugrin et al., 2014).

Advancements in Video Forgery Detection: Novel Methods for Object and Facial Forgery Detection Using Temporal and Spatial Analysis

Authors- Kasarla. Rajiv Reddy, Kaipa Roopesh Kumar Reddy, Sathineni. Sai Pranav Reddy

Abstract- With the advent of sophisticated yet easy to use video editing and forgery tools, detection of malicious editing and forgery in digital videos is becoming increasingly challenging as development of forensic investigation tools for authenticating the integrity of digital videos has lagged behind. The work reported in thesis explores four novel methods aimed towards detecting object and facial forgeries in video: temporal-RNN, spatial-RNN, fRNN, and lightweight 3DRNN. The temporal-RNN and spatial-RNN methods are designed for comprehensive detection of object-based forgeries. They analyse temporal and spatial features within a video in order to detect forged frames within a video and to mark forged regions within forged frames. The benefits of proposed detectors were exhaustively verified using recent object based forged video datasets under various testing scenarios. Significant improvements in detection performance and forged region localization were observed in comparison to existing detection methods. A frequency-based RNN is developed to identify facially manipulated videos (such as Deep Fakes, Face Swap andFace2Face). The shallow fRNN architecture was verified for binary and multi-class forgery detection on recent datasets. The fRNN was also benchmarked on the Face Forensics++ platform and binary detection performance of fRNN was found to be better than existing machine learning and deep learning based detectors. A lightweight 3DRNN is designed to detect the facially manipulated videos. The detector utilizes the combined effect of spatial and temporal features in a unique manner to label the given video as forged. The 3DRNN architecture ensures low computational complexity in terms of number of trainable parameters, making it a good choice for deployment in memory and resource constraint devices such as smartphones. The method also performed well against low quality, highly compressed videos that are commonly found across social media.

DOI: /10.61463/ijset.vol.12.issue3.179

Intellisafe Rideguard

Authors- Research Scholar Riya Lohiya, Research Scholar Rishika Jain, Research Scholar Rohit Choudhary, Research Scholar Raghvendra S. Evaney, Professor Dr. Monika Kapoor

Abstract- Everyday around the world a large percentage of people die from road accident, especially in case of two wheelers. This may be avoided by emergency treatment of victim, wearing helmets and riding vehicles without consuming alcohol. An effective approach is made to solve the problem by using Smart Helmet. Here, Smart Helmet is acting as a key. If the driver has consumed alcohol, the sensor will sense it and immediately lock the engine. Smart helmet provides help in case of accident by using GSM and GPS technology. If the person is met with an accident, then in such situation a message along with the location is sent to the ambulance or family member so that medical aid can be provided to that person as soon as possible. The project aims at intelligence security providing awareness for wearing helmet and provides prevention for human life safety.

AuthCrypt: A Secure Password Manager Built on Flutter

Authors- Professor Pankaja Kadalagi, Faizan Fayaz Mir, Prerna Phakire

Abstract- In cloud computing for optimized workflow scheduling, it is crucial to meet user deadlines while minimizing the cost of resources. This paper is a novel approach that compares Ant Colony Optimization (ACO) with the Buddy System in reducing the cost of the resources used for scheduling those workflows. Ant Colony Optimization was inspired by the behavior of ants in their search for food using pheromone chemicals released by them. Thus, the ACO algorithm is employed to find the solution space and then explore it to find the near- optimal solution among them. Meanwhile, Buddy System algorithms efficiently handle the allocation and deallocation of resources in the cloud. In the cloud system, the Buddy System can be used to allocate and deallocate VM (virtual machine) instances.

Design and Implementation of Automated Staircase for Handicap Person

Authors- Assistant Professor Ghanshyam P. Dhalwar, Assistant Professor Vipin S. Khangar

Abstract- The stair a case lift is a mechanical device that helps lifts persons and wheelchairs up and down stairs when they may have trouble doing so on their own. A rail is attached to the stair treads of adequately wide stairs. The rail has a chair or raising platform attached to it. The primary goal of this project is to create on both an indoor and outdoor stairlift. A chair that moves up and down a staircase on a motorised rail is known as a stair lift. Elements that maximise ease of use, comfort, and attractiveness in the house, a secure and inexpensive place to live method to address the specific requirements and difficulties that on the stairs, individuals have experiences. The portable stair-lift a mobility aid in the shape of a chair affixed to one side of Stairways facilitates elderly access between floors.

Efficacy of Salvodera Persica Fruit as Corrosion Inhibitor on Mild Steel in Hydrochloric Acid Solution

Authors- Research Scholar Neha Manwani, Professor Dr. Manoj Batra, Professor Dr. S.K. Arora, Retired Professor Dr. R.K.Upadhyay

Abstract- The inhibition actions of ethanolic extract of Salvodera persica fruit for mild steel surface in HCl has been studied by weight loss, gasometric method, and thermometric method. Inhibition efficiency was studied in different concentration of acid with different concentration of inhibitor ( 0.2%,0.4%,0.6%,0.8%). Inhibition efficiency was found to be increase with increase in concentration of inhibitor and acid. The adsorption of ethanolic extract of Salvodera persica fruit on to mild steel surface pursued that as indicated by Langmuir model. This study showed that this particular plant extract is an effective inhibitor in suppressing the corrosion on the surface of the metal.

DOI: /10.61463/ijset.vol.12.issue3.181

IOT Based Smart Irrigation System

Authors- Aman Sahu, Abhishek Sharma, Akshay Khandelawal, Anurag Pal

Abstract- Agriculture is a crucial sector of the economy in many countries. However, conventional irrigation systems are not efficient in terms of water usage and control. To overcome these issues, an IoT-based smart irrigation system is proposed in this project. The proposed system consists of a network of sensors and actuators that collect data on soil moisture, temperature, humidity, and weather conditions. This data is transmitted to a central control unit that uses algorithms to make decisions about when and how much water to be irrigated. The system is designed to be energy-efficient and cost- effective, using a regular power source to operate. The system provides several benefits over traditional irrigation systems. It reduces water wastage and conserves water resources, resulting in improved crop yields and reduced costs. The system is easy to install, operate, and maintain, and can be customized to suit specific crops and soil types. Additionally, the system is scalable and can be expanded to cover larger areas or multiple fields. Overall, the proposed IoT-based smart irrigation system is a significant improvement over traditional irrigation systems, providing a sustainable and efficient solution for agriculture. the system’s scalability, energy-efficiency, and customizability make it a viable option for farmers looking to adopt new technology to improve their irrigation systems. first, it reduces water wastage and conserves water resources by only irrigating when needed. This, in turn, results in improved crop yields and reduced costs. Second, the system is easy to install, operate, and maintain.

Placement Cell Management System

Authors- Ayush Kumar, Karan Joshi, Ankit Jeena, Akhil Patwal, Assistant Professor Shantanu Pant

Abstract- In today’s competitive job market, the role of university placement cells is crucial as they give the opportunities to students so that they can make their successful transition from academia to workforce. This research paper proposes the development and implementation of a comprehensive Placement Cell Management System aimed at enhancing the efficiency and effectiveness of university placement processes. The proposed system has the various functionalities including student registration, employer engagement, job posting and application management, interview scheduling, and alumni networking. By using the principles of information technology, data analytics, and user- centered design, the Placement Cell Management System aims to streamline the entire placement process, from initial registration to final placement, thereby reducing manual efforts, minimizing redundancies, and improving overall productivity. Furthermore, the paper discusses the potential benefits of the Placement Cell Management System, such as improved student placement rates, enhanced employer satisfaction, and better alumni engagement. The research also addresses challenges in system implementation, including data security, user training, and scalability. Through a combination of theoretical analysis, case studies, and empirical research, this paper aims to provide insights into the design, development, and deployment of an effective Placement Cell Management System, contributing to the advancement of university-industry collaboration and student career development initiatives.

Smart Blind Stick for Handicap

Authors- Research Scholar Ritika Kumari, Research Scholar Rewa Pawar, Research Scholar Nikhil Kumar, Research Scholar Mohd.Shahfahad, Professor Shraddha Shrivastava

Abstract- IA smart stick concept is devised to provide a smart electronic aid for blind people . Blind and visually impaired find difficulties in detecting obstacles during walking in the street. The system is intended to provide artificial vision and object detection, real time assistance via making use of Arduino UNO. The main objective of our project is to provide a sound based assistance to blind people. While the user moves the stick in the forward direction, the ultrasonic sensor with.

DOI: /10.61463/ijset.vol.12.issue3.180

Detection of LPG Gas Leakage Using IoT

Authors- Vishal Dharpure, Vikrant, Subodh Kumar, Swarnim Lade, Associate Professor Arun Patel

Abstract- For a variety of reasons—economic, convenience, or preference—LPG is a popular choice for cooking in many nations. This study explores the application of the Internet of Things (IoT) to monitor and display the gasoline content of a residential LPG cylinder. This approach not only facilitates the automatic booking of new LPG cylinders but also enables the detection of gas leaks. Given that the LPG capacity within a cylinder is seldom checked, our system aims to accurately display the LPG level. We utilize a load sensor (SEN-10245) to measure the LPG level, with its output connected to an Arduino Nano board. The gathered data is then relayed to the user via SMS (short message service), and new cylinder bookings are automatically processed by calling the registered gas booking number using a GSM module. To detect gas leaks, we employ a gas sensor (MQ-6). This setup allows real-time monitoring of the LPG level, which is displayed on an LCD screen. Furthermore, from the activation date, we can track the LPG usage duration. When the LPG level drops to a critical threshold (below 20%), the system alerts the user through an IoT-based notification sent to their mobile phone.

<strongIntegrating Wireless Sensor Networks, IoT, and Cloud Computing for Real Time Application

Authors- M.tech. Scholar Shilpa W. Mate, Professor Dr.N.K. Choudhari

Abstract-This paper presents the design of a model of a wireless moisture and water tank level indicator as a sensor node which monitor based on wireless sensor network (WSN) and information is updated on cloud. The user-controller provided with information from the receiver board (master) that transmitted sensors data (as current parameter of water tank level and soil moisture level through the transmitter board (slave). The receiver board AT89C51 used to receive a real time sensor data from a transmitter to a PC monitor via serial connection and forming a database for future uses. The system uses Arduino nano, moisture sensor, ultrasonic sensor, nodemcu and transceiver RF module.

IoT Based Smart Attendance System Using RFID and Google Sheet

Authors- Sanskar Soni, Anurag Soni, Ayush Sharma, Ashwini Anand, Dr. Kamna Mishra, Professor Shraddha Shrivastava

Abstract-The traditional manual attendance system is very time-consuming, It is insecure and this system can lead to human errors. This system is ineffective as our valuable time and work get wasted in organizing attendance on pen and paper. Hence to overcome this problem we have used a relational database system to store the real-time data of the students. For this project, we used RFID tags and readers to record the attendance of the students. To manipulate and represent the data based on the unique RFID tags, which get fast and easily scanned on the RFID reader [1] RFID technology is an automatic wireless identification system. This particular system works with active and passive RFID cards and a reader. In this work, we have tried to erase the problem of manually taking attendance with the use of RFID technology. This system is used to help the authority manage the attendance of students in a more organized, efficient, and time-saving manner. This particular system has been implemented in a prototype system that uses RFID tags and a reader to calculate attendance which proves its effectiveness over the normal attendance approach. The design of the system is simple, not expensive, and portable to use which makes it good for candidates and also for commercial and academic purposes ransportation more accessible.

An Attempt to Develop an Efficient Budget-Friendly Semi-Automatic Dishwasher with an Ultrasonic Soap Dispensing System for Kitchen Utensils

Authors- Sekar K S

Abstract-Nowadays, all large families have been divided into many nuclear families. Even women in the family need to work and generate money to support their families. Women depart for the office in the early morning and return in the late evening. As a result, they struggle to keep up with household duties. Many inventions have been developed to make such tasks simpler like washing machine, vacuum cleaner and so on. One such item is a dishwasher. Dishwashing is one of the most necessary and unpleasant home duties. The machine is used to simplify the process and save time and effort. The present work is a novel approach to develop a low-cost semi-automatic dishwasher with improved cleaning efficiency, reduced water and power consumption. This equipment is designed using CREO Modeling software. The developed machine was tested and worked fine.

Hand Signs to Audio Converter

Authors- Raghwendra Kumar Pandey, Manoj Kumar Thakur, Anish Thakur, Rahul, Saurabh Agarwal, Assistant Professor Mukesh Bharadwaj

Abstract-Individuals primarily communicate with one another. Blind and deaf people use sign language to communicate with others. These individuals have difficulty communicating their message to ordinary people. Deaf and blind people believe they are unable to communicate because of a lack of communication skills, and as a result, they are unable to express their emotions. Because most individuals aren’t educated in sign language, communicating in an emergency can be extremely challenging. As a consequence, the challenge may be solved by converting hand gestures into human-hearing sounds and text. Vision and non-vision approaches are two of the most commonly used methods for detecting hand movements or gestures. In a vision-based approach, a camera will be used for gesture detection, whereas sensors will be employed in a non-vision-based technique. In this study, a vision-based technique was used. This device detects and locates hand motions in order to keep a communication channel open with others. Using convolutional neural networks and artificial neural networks, this research develops a gesture recognition system. This study looks into the advantages and disadvantages of hand motion recognition.

Laser Security Alarm System

Authors- Yash Pathak, Suraj Kumar, Aryan Raj, Yash Singh, Associate Professor Arun Patel

Abstract-Laser security alarm systems are integral to ensuring safety and security in residential, commercial, and industrial environments. These systems utilize laser diodes and photo detectors to create an invisible barrier, triggering an alarm upon detection of unauthorized entry or breaches. However, accurately monitoring and managing security breaches can be challenging without real-time data and remote accessibility. This paper explores the design, implementation, and benefits of integrating IoT technology with laser security alarm systems. By enabling remote monitoring and management via internet-connected devices, IoT integration enhances the effectiveness and responsiveness of security systems. Real-time alerts and data analysis capabilities empower users to take prompt action, improving overall security protocols. Through case studies and analysis, this paper demonstrates the transformative potential of IoT-based laser security alarm systems in enhancing safety practices and protecting lives and property.

Glasses for Blind Person

Authors- Research Scholar Vikash Sharma, Research Scholar Shriddha Gautam, Research Scholar Vatsal Kashyap, Research Scholar Utkarsh Agrawal, Professor Ravi Bhushan Roy

Abstract-Glasses for blind person is an innovative and cost effective Arduino-based radar system that operates on the principle of echolocation. Echolocation is an acoustical process which is used to locate and identify a target by sending sound pulses and receiving the echoes reflected back from the target. Echolocation is used by several mammals including dolphins, whales, and bats. RADAR stands for Radio Detection and Ranging. And since radar relies on echoes and reflections of sound pulses, echolocation technology is used in radar. Our Model is designed to help visually impaired individuals in a cost efficient manner. It is achieved using Arduino nano, Ultrasonic sensor, piezo electric buzzer and power source. These glasses provide its range in all direction and detect obstacles in its range. The Ultrasonic sensor any object/person in front of the person wearing the glasses and then passes the signal to Arduino nano and further acknowledges the visually impaired individuals by the means of buzzer. This helps in preventing unwanted clashes or accidents.

Visionary Diagnosis: Deep Learning Approach with VGG16 and Image Net for Eye Disease Classification

Authors- Ms. Prajakta V. Shintre

Abstract-Globally, retinal disease represents a considerable risk to vision health, emphasizing the critical need for current strategies to ensure effective treatment. Recently, deep learning methods have shown promise in automating the detection and diagnosis of retinal diseases from medical images. The paper explores the pre-trained VGG16 convolutional neural network (CNN) architecture, originally trained on the ImageNet dataset, for categorizing eye disease from fundus images. After calculating the working of the VGG16 model in distinguishing between healthy and diseased retinas and analyzing those results with another deep learning design for medical figures or image examination used in general [8]. Our findings demonstrate the strength of the VGG16 model in accurately identifying retinal diseases, highlighting its potential as a helpful appliance for early disease classification and scientific decision support [15].

Food Calorie Estimation Using Deep Learning Neural Network

Authors- Priyanka. N. Sorte

Abstract-As food becomes more accessible, the prevalence of obesity is rising, which is a serious chronic disease. Maintaining good health requires precise monitoring of caloric intake. Traditional methods, nevertheless, could be tedious and wasteful. Calorie estimation from food photos using deep learning neural networks is the subject of this research. We provide a technique that analyses food images using Deep Neural Network (DNN) to calculate calorie content. Deep Neural Network (DNN) is with 22 layers to accurately identify the food in the system. A massive collection of tagged food pictures with calorie information is used to train the DNN. As part of the training process, the model extracts shape, colour, and texture information from the images, and then converts it to calorie content. One of the many advantages of this technology is that it provides calorie estimates more efficiently and without invasiveness than manual methods. To further assist with dietary tracking and weight management goals, it may also be integrated with mobile applications. Properly evaluating calorie content for complex recipes with several components is difficult, and obtaining high-quality and diverse training data to avoid bias is another difficulty. When compared to the state-of-the-art method, the suggested approach performs better.

IOT Based LPG Gas Leakage Detection System

Authors- Kirti Nigam, Manuraj Singh Thakur, Jatin Yadav, Juhi Saxena, Assiatant Professor Dr. Prashant

Abstract-Liquefied Petroleum Gas (LPG) is a main source of fuel, especially in urban areas because it is clean compared to firewood and charcoal. Gas leakage is a major problem in the industrial sector, residential premises, etc. Nowadays, home security has become a major issue because of increasing gas leakage. Gas leakage is a source of great anxiety with ateliers, residential areas and vehicles like Compressed Natural Gas (CNG), buses, and cars which are run on gas power. One of the preventive methods to stop accidents associated with the gas leakage is to install a gas leakage detection kit at vulnerable places. The aim of this paper is to propose and discuss a design of a gas leakage detection system that can automatically detect, alert and control gas leakage. This proposed system also includes an alerting system for the users. The system is based on a sensor that easily detects a gas leakage.

Object Avoidance Robot

Authors- Anshika Samaiya, Aditya Prasad, Anshika Pali, Divya Panjwani, Professor Sourabh Pandey

Abstract-An object-avoidance robot is an important part of autonomous systems designed to navigate the environment while avoiding obstacles. The object avoidance robot’s design has a sensors, primarily an ultrasonic sensor that detects obstacles in its vicinity. These sensors allow for distance measurements, which allow the robot to make informed navigation decisions. The Arduino microcontroller processes the sensor data and implements control algorithms to steer the robot away from detected obstacles. The main parts of the proposed object avoidance robot include motor drivers for motion control, power supply and frame to support the structure. The software architecture includes sensor interface code, obstacle detection algorithms, and motor control logic. Implementation includes hardware component integration, software module development, and iterative testing to improve performance. The efficiency of the object avoidance robot is based on the robustness of the obstacle detection algorithms, the accuracy of the sensor measurements, and the efficiency of the control logic. Challenges such as sensor noise, environmental changes, and real-time processing limitations require careful planning. Potential applications for an object- avoidance robot span a number of different fields, including surveillance, environmental monitoring, and assistive robotics. Leveraging the accessibility and community support of the Arduino platform, this project aims to provide a practical framework for developing cost-effective and customizable object avoidance robots.

Automatic Irrigation System

Authors- Hemant Mewada, Ishita Deep, Mayank Malviya, Khushi Gupta, Associate Professor Dr Vijay Yadav

Abstract-Watering the Farm land is the most important cultural practice and one of the labor intensive tasks in daily greenhouse operation. irrigation systems ease the burden of getting water to plants when they need it. Knowing when and how much to water is two important aspects of watering process. To make the gardener works easily, the automatic irrigation system is created. There have a various type using automatic irrigation system that are by using sprinkler system, tube, nozzles and other. This system uses watering sprinkler system because it can water the crops located in the field. This project uses Arduino board, which consists of ATmega328 Microcontroller. It is programmed in such a way that it will sense the moisture level of the crops and supply the water when required. This type of system is often used for general crops care, as part of caring for small and large gardens. Normally, the crops need to be watered twice daily, morning and evening. So, the microcontroller has to be coded to water the plants in the garden or farms about two times per day. People enjoy plants, their benefits and the feeling related to nurturing them. However for most people it becomes challenging to keep them healthy and alive. To accommodate this challenge we have developed a prototype, which makes a plant more self-sufficient, watering itself from a large water tank and providing itself with artificial sunlight. The pro-To type reports status of its current conditions and also reminds the user to refill the water tank. The system automation is designed to be assistive to the user. We hope that through this prototype people will enjoy having plants without the challenges related to absent or forgetfulness.

Object Avoidance Robot

Authors- Abhay Raj Rana, Aditya Raj Patel, Akshat Pandey, Anmol Gupta, Professor Dr.Umashankar Kurmi

Abstract-The growing demand for safer roads has prompted many companies to do so develop complete self-driving cars. A self-driving car requires a lot various sensors such as gyroscopes, radars, GPS, total stations, etc. and advanced software. This work will focus on the possibilities of using only light sensing devices for a tracking bot and explore its pros and cons. The purpose is to find out which type of light sensor is more suitable for tracking robot and what are the limitations of a tracking robot using this technology. A demonstrator using two light sensors to control speed and direction and a color sensor will be built to avoid obstacles. In addition to choosing the most suitable sensor for the light tracking robot sensing distance and range of the selected will be tested. Explore different light tracking options and accuracy demonstrator, the vehicle will be placed in an open interior with arranged colors light barriers. The robot will be tested both in a completely dark room and in a lighted room room The intention of the result is to see the differences in the behavior of the robots when interference from ambient light is added as another aspect. Test results are presented and the use of different sensors is discussed. The final conclusion about using light sensing in a tracking robot is that it is easy and inexpensive method but should be used as a supplement to other sensing devices not as a separate method.

IOT Based Agriculture System Using Node MCU

Authors- Professor Prashant Chaturvedi, Research Scholar Darshita Dongre, Research Scholar Ankita Bhardwaj, Research Scholar Aman Verma, Research Scholar Abhishek Kr Tiwari

Abstract-The integration of Internet of Things (IoT) technology into agriculture has the potential to significantly enhance productivity, resource management, and sustainability. This paper presents an IoT-based agriculture system utilizing the Node MCU platform, which leverages its Wi-Fi capabilities and ease of programming to create a cost-effective, scalable solution for modern farming. The proposed system consists of a network of sensors and actuators to monitor and manage key environmental parameters such as soil moisture, temperature, humidity, and light intensity. Data collected by the sensors is transmitted in real-time to a cloud-based server via the Node MCU, where it is processed and analyzed to inform decision-making processes. Actuators are employed to automate irrigation and other critical agricultural activities based on sensor feedback, thereby optimizing water usage and improving crop health. This system also includes a user-friendly interface that allows farmers to remotely monitor field conditions and control the actuators using a smartphone or computer. The implementation of the Node MCU-based IoT system demonstrates significant improvements in operational efficiency, resource conservation, and crop yield, highlighting its potential as a vital tool for the advancement of smart agriculture.

Solution for Sustainable Energy Harvesting

Authors- Nikhil Mote, Rutik Raut, Nishant Virkar, Viraj Nikam, Professor Uchale Bhagwat

Abstract-Energy harvesting, a process of capturing ambient waste energy and converting it into usable electricity, has been garnering significant attention due to the limitations of traditional power sources. In our project, we have harnessed this technology by fabricating flexible piezoelectric composite discs. The study investigates the performance of these discs, which incorporate lead zirconate titanate (PZT) powder with particle sizes of 3 µm and 1 µm,multiwalled carbon nanotubes (MWCNT) with diameters of 5–20 nm and lengths up to 10 µm, and polydimethylsiloxane (PDMS) synthetic silicone rubber. Solvents such as THF and chloroform were utilized in the preparation process. The composite discs weretested for their peak performance, lifetime, and durability under various conditions. The primary objective of our research is to extract usable power to operate low-power devices, including mobile devices and wireless sensor networks, and to support the recent advancements in extremely low-power electrical and mechanical devices such as micro-electromechanical systems (MEMS).

Intoxication Sensing Device

Authors- Shivang Gupta, Taranjeet Kaur, Veer Pratap Singh Rathore, Yashovardhan Singh, Associate Professor Dr. Zahid Alam

Abstract-This paper presents the design and development of an intoxication sensor device using an Arduino Uno, LCD display, MQ sensor, LED, and buzzer. The device is engineered to detect the presence of alcohol in the environment and provide visual and auditory alerts if the alcohol concentration exceeds a predefined threshold. The primary objective is to create a cost-effective, reliable, and portable solution for alcohol detection to enhance public safety and prevent alcohol-related incidents. Key findings demonstrate the device’s accuracy, responsiveness, and potential applications in various settings such as workplaces, public transportation, and vehicles.

A Review on Sustainable Packaging and Printing Ecosystem

Authors- Uday Choudhary, Associate Professor Srivani Thadepalli

Abstract-In response to the growing global emphasis on sustainability, the packaging and printing ecosystem has witnessed a remarkable shift towards more eco-conscious practices. This comprehensive review paper, titled “A Review on Sustainable Packaging and Printing Ecosystem: A Study on Design, Materials, and Economical and Operational Aspects,” provides a thorough examination of the multifaceted dimensions shaping the sustainable evolution of packaging and printing industries. At its core, this review paper delves into the intricate relationship between design, materials, and the economic and operational aspects of these industries. It draws upon insights from selected studies to offer a holistic understanding of the key components driving sustainability in packaging and printing. One pivotal aspect explored in this review is the concept of “Design for Sustainability.” It illuminates innovative design strategies that prioritise reducing environmental impact, minimizing waste, and embracing the principles of a circular economy. Furthermore, the paper underscores the importance of user-friendly design approaches that align with eco-conscious practices. Materials play a central role in the pursuit of sustainability, and this review scrutinizes the adoption of sustainable alternatives. It sheds light on materials such as biodegradable polymers, cellulose nanofibers, and natural fibers, examining their environmental benefits and challenges in detail. Economic considerations are another critical facet discussed within the paper. It delves into the economic implications of sustainable packaging and printing, addressing issues of cost-effectiveness, resource conservation, and the competitive advantages that sustainability can confer in the market. Operational efficiency is also a key focus of this review, offering insights into how sustainable practices impact the day-to-day operations of packaging and printing industries. This includes discussions on efficiency gains, reduced energy consumption, and effective waste management. Technological advancements are highlighted as well, with an emphasis on cutting-edge innovations such as smart packaging and 3D printing. These technologies are shown to contribute significantly to sustainability efforts by enhancing product monitoring, traceability, and the development of intelligent materials. In essence, this review paper presents a comprehensive and cohesive perspective on the journey towards sustainability within the packaging and printing ecosystem. By synthesizing insights from diverse research areas, it aims to provide a roadmap for industry stakeholders to navigate the evolving landscape of environmentally responsible and economically viable solutions.

Shape-Guided Conditional Image Synthesis for Tooth Alignment

Authors- Anand Gupta, Deep Mehta, Arpan Dholakiya, Soorajkumar Suresh, Siddhant Jadhav, Amit Yadav, Yaduvir Singh

Abstract-Orthodontics is a field of dentistry that focuses on correcting misaligned teeth. Orthodontic treatment often involves the use of braces, aligners, retainers, and other dental appliances to align teeth, correct bite issues, and improve overall dental health and aesthetics. But fixing them can be a long and complicated process. So, it’s important to have a picture showing what your teeth will look like after treatment. This helps dentists explain things better and makes patients more likely to go through with the treatment. In this paper, we present an approach for generating the conditional image of a misaligned tooth to an aligned tooth from a diffusion model it takes 2D images as input (e.g., captured by the camera, or smartphones), and aligns the teeth part in the image within 2D image space to generate post-treatment like images, our method employs 3D STL data scanned by intra-oral scanner projecting pre- and post-treatment, diffusion model to learn the spatial movement of each tooth followed by post-processing to convert the teeth area more realistic textures. We validate our pipeline over various facial photographs, illustrating its outstanding effectiveness and broad utility within the field of Orthodontics.

The Evolution of Artificial Intelligence – A Comprehensive Review

Authors- Twinkle Sharma, Poonam, Renuka Arora

Abstract- This research paper offers a comprehensive exploration of the evolutionary journey and multifaceted impact of Artificial Intelligence (AI) on contemporary society. Beginning with the philosophical roots and historical milestones, the paper delves into the first wave of AI, marked by rule-based systems, followed by the challenging AI Winter of the 1980s-1990s. The resurgence of interest in the late 1990s, particularly with the advent of machine learning and neural networks, sets the stage for the transformative phase in AI. The convergence of big data and AI ushers in an era of innovation, with breakthroughs in machine learning algorithms and successful applications across diverse domains. The paper highlights the pivotal role of deep learning and the advancements in neural network architectures, discussing the roles of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Applications of deep learning in healthcare and finance exemplify the real-world impact of AI. Ethical considerations in AI autonomy, challenges in implementation, and the responsible use of AI are addressed, providing a holistic perspective on the current AI landscape. The exploration extends to the future trajectories of AI, discussing emerging trends, such as federated learning and Explainable AI (XAI), and envisioning the role of AI in addressing global challenges. In conclusion, the paper emphasises the importance of responsible AI development and deployment in navigating the dynamic relationship between artificial intelligence and human progress. As we embark on future trajectories, understanding the ethical considerations, embracing emerging trends, and addressing global challenges will be pivotal in shaping a positive and equitable AI-driven future.

A Study on Impact of Restaurant Features and Average Dining Cost on Customer Satisfaction

Authors- Twinkle Sharma, Poonam, Renuka Arora

Abstract- India has always been a food-loving country with each region having its own special cuisine. Indians have never been very big on eating out. But all that is changing now. The restaurant industry in India has been growing at a rapid pace over the last decade or so and the growth story is set to continue for the upcoming future. There were nearly 220K good restaurant establishments in India in 2002. The food service or restaurant industry was worth a whopping Rs.43, 000 crores in 2010 and growing at a healthy rate of 15-20% annually. Full-service restaurants are under more pressure than ever, in part because the restaurant business has seen strong growth in the home-meal-replacement concept in recent years. We searched nearly 8653 restaurants that come under the famous “zomato restaurants”. This investigation focused on two factors: (1) Average cost of dining for Two,(2) Customer satisfaction, To analyse this relationship among the cost and customer satisfaction, we attempt to present multistate cost and customer satisfaction analysis. We have to categorise an analysis based on effective cost slabs along with services provided for customer satisfaction on that particular slab. To analyse this investigation we used the online version of the tool provided by IBM that is IBM Cognos.

Automatic Water Level Monitoring System

Authors- Deepali Gupta, Dimpal Singh, Anshu Kumar, Aaditya Raj, Associate Professor Arun Patel

Abstract- Generally most of the houses depends upon the overhead tanks as the main source of water. People generally switch on the motor when their taps go dry and switch off the motor when the tank starts overflowing. This results in unnecessary wastage of water and sometimes non-availability of water in emergency. This phenomenon is commonly seen in both Urban and rural areas and this needs to controlled by monitoring water level in the tank, here we need a mechanism capable of switching on the motor when the water level in the tank goes low and switching it off as soon as the water level reaches a maximum level. Automatic water level control can be achieved by monitoring and keeping track of water level with the help of electronic sensors and controllers. Ultrasonic sensor is used to monitor the water level by calculating round trip time of echo from transmitter to water surface. Water level obtained from ultrasonic sensor is given to Arduino, where all the calculations and decisions are made. Arduino generate a signal to turn on/off the motor based on water level. This on/off signal and the water level should be communicated to the motor by using RF module where radio waves are used as the means of communication. The motor will be controlled automatically based on the water level in the tank.

IOT Home Automation System

Authors- Yash Shrivastava, Arushi Adhruj, Archi Vatab, Piyush Mishra, Dr. Vijay Yadav, Professor Shraddha Shrivastava

Abstract- Internet of Things (IOT) conceptualizes he idea of remotely connecting and monitoring real world objects through the internet. When it comes to our house, this concept can be incorporated to make it smarter, safer and automated. This IOT project focuses on a smart wireless home security system which sends alerts to the owner by using Internet in case of any trespass and raises an alarm optionally. Besides, the same can also be utilized for home automation by using same set of sensors. The Internet of Things (IOT) belief system looked as an exceptionally unique and radically distributed networked system composed of a very large number of identifiable smart objects. These objects can convey and interface among themselves, with end-users or different elements in the system. The proposed system reduces the resources like manpower and time In this project, IOT technology has been adopted in which internet used as a tool to connect and exchange the data among the different types of devices.

Investigation on Flow over Conventional and Supercritical Airfoils at Transonic Regimes

Authors- Mysa Koushik

Abstract- Flow over conventional and supercritical airfoils in the transonic regime is investigated and compared in this study. This study focuses on two-dimensional flow conditions with Mach numbers of 0.8 and 0.9 at Angles of attack (α)00 and 50. Flow over NACA4415 and SC(2)-0410 as examined using the Ansys software by CFD analysis. The computational results indicate that a supercritical airfoil has higher efficiency and performance and delays the formation of shock waves compared with conventional airfoils in the transonic regime. The Mach number and angle of attack affect the generation of shock waves on both airfoil surfaces. SC(2)-0410 and NACA-4415 were compared by considering factors like lift co-efficient CL, drag coefficient C¬D, lift to drag ratio(L/D), and position of formation of the shock wave on the airfoil surface. The behavior of the airfoils in the transonic flow regime was further analysed.

DOI: /10.61463/ijset.vol.12.issue3.182

Design and Analysis of Highway Deck Slab Bridge with Prediction of its Durability

Authors- Shubham Kumar Pandit, Professor Dr. J.N. Vyas

Abstract-Suspension bridge is an efficient structural system particularly for large spans. Many difficulties related to design and construction feasibility arises due to its long central span. There are many suspension bridges around the world and dynamic behaviour has been found to be the primary concern for those bridges. Natural period of a suspension bridge mainly dependent on the span and other structural dimensions related to the stiffness.. In the study, we observed various design and analysis of the deck slab for suspension bridge under different types of loading in the software based on IS provisions to carried out the deflected shapes and impact on the deck slab. On the technical drawings, reinforced concrete slabs are often abbreviated to “R.C.C. slab” or simply “R.C.” Technical drawings are often created by structural Engineers who use software such as STAAD pro software.

Modelling, Simulation and Ann Recognition of Power Quality Disturbances in Photovoltaic Grid Connected System

Authors- Jibrin Adaji Hassan, A. L. Amoo, Ehiagwina Elijah. Omizegba, D. M. Nazif

Abstract-In achieving global decarbonization goals through renewable energy resources (RES), there is an increase concern over the quality of electric power emanating from these non- conventional resources that cause electric power quality disturbances (PQD) notably: grid synchronization instability, outages, islanding, voltage sag, voltage swell, harmonics etc. To conceptualize related issues accentuated, the grid- side of a grid-connected Photovoltaic (PV) system is designed, modelled and simulated using MATLAB/Simulink environment. The developed model implements all components for synchronizing the PV system with the grid which includes: a three-phase Voltage Source Inverter (VSI), a grid filter, grid synchronization and VSI controller and each component of the system is modelled, simulated and validated over certain operating scenarios of the PV system controller under specific grid and weather conditions. The model developed has been validated with IEEE P1547 standard that covers the interconnectivity of distributed generation renewable energy resources. It is envisioned to bring about effective mitigation of the disturbances in the systems through compensation techniques. The simulation results show that, the model is simple, reliable, stable and suitable for implementation of the grid- connected PV system.

Research Paper on Artificial Intelligence

Authors- Sarthak Tyagi

Abstract-In achieving global decarbonization goals through renewable energy resources (RES), there is an increase concern over the quality of eThe mere existence of artificial Intelligence has made multiple changes throughout the world, not only in computer science but in multiple fields. This paper presents the research on applications of artificial intelligence, definition, history, growth, and future possibilities.

IOT Based Home Automation

Authors- Aditya Kumar Jha, Aditya Kumar, Abhishek Meena, Abhishek Singh, Associate Professor Dr Rakesh Agrawal

Abstract-The Internet of Things (IoT) has revolutionized various sectors, including home automation. This paper explores the architecture, benefits, challenges, and future prospects of IoT-based home automation systems. By leveraging IoT technologies, home automation promises enhanced convenience, energy efficiency, security, and comfort. This paper provides a comprehensive overview of IoT-based home automation, examining the technical aspects, potential applications, and emerging trends in this rapidly evolving field.

Ultrasonic Smart Dustbin

Authors- Reserach Scholar Dolly Dhote, Reserach Scholar Ankit Kumar, Reserach Scholar Ayush Arya, Reserach Scholar Divyanshu Gupta, professor Sunny Jain

Abstract-Mymensingh is the capital of Mymensingh Division in central Bangladesh. Ensuring water sanitation and hygiene in Mymensingh is vital for community health, requiring effective measures and collaboration between authorities, organizations, and residents for sustainable implementation. The objectives of this study were to investigate the water supply and sanitation status of Mymensingh City. Data were collected primarily based on a reconnaissance survey with the help of a structured questionnaire. A cross-sectional survey design was employed to collect data on variables related to water, sanitation, and hygiene in the area. Many homes rely on submersible pumps and deep tube wells for drinking water, while access to piped water is limited. Inadequate water supply and limited access to clean water contribute to waterborne illnesses and negatively impact public health. Sanitation infrastructure in Mymensingh City Corporation varies, with reliance on septic tanks and pit latrines, while limited sewage systems and waste management exist. Inconsistent hygiene practices contribute to waterborne illnesses, highlighting the need for improved infrastructure and behavior change interventions. Improving the drainage system, implementing effective measures for waste management, and promoting hygiene education programs are essential for minimizing waterborne diseases and enhancing residents’ quality of life.

Assessment of Physicochemical Analysis of Acalypha Indica Linn

Authors- Research Scholar Dr. S. Senthil Kumar, Dr. C. Kiruba Rani

Abstract-The present study of physicochemical parameters like extractive of plant with different Solvents, Determination of moisture content, Analysis of ash values in Acalypha indica. The percentage of extractive values was maximum in ethanol (61%) followed by water (13%) and chloroform (8%). The petroleum ether extract showed low yield (5%). The total ash content was 9.6% and water soluble ash content was more than that of acid insoluble ash. The sulphated ash content was recorded as 10.2%. the ash values and purity of the plant sample.

Applications of Quantum Dots

Authors- Tanmay Hadke

Abstract-Quantum dots are also called fluorescent nanocrystals that play an important role in biologi- cal and bio-medical fields. They are well-known for their drug-delivering capabilities and cellular imaging. In electronics perspective, quantum dots act as semiconductor nanoparticles that ex- hibit unique optical properties such as size- controlled fluorescence that is being used in quantum dot televisions, high quantum yields, and stability against photo bleaching. Carbon being a very important element in chemistry has an important role in the applications of quantum dots as well. Graphene, a carbon compound, is introduced with the concept of Graphene Quantum Dot or GQD.

Optimisation of Counterflow Heat Exchanger Using Box Behnken Design

Authors- Neeraj Gupta, Dr. B.K. Chourasia

Abstract-This study focuses on the optimization of counter flow heat exchangers using the Box-Behnken design (BBD), a response surface methodology (RSM) approach for experimental design. Counter flow heat exchangers are widely utilized in various industrial processes due to their high efficiency in thermal energy transfer. However, optimizing their performance involves multiple parameters, including fluid flow rates, temperature differences, and heat transfer coefficients. The Box-Behnken design offers a systematic and efficient way to explore the effects of these variables and their interactions on the performance of heat exchangers. Our study shows higher value of effectiveness of counter flow heat exchanger as compared to the study of Sridharan (2021) and Patel and Singh, (2023). The application of RSM based BBD method improves the effectiveness of counter flow heat exchanger.

Simulation and Efficiency Enhancement of Solar PV Panel Using Cooling Fins

Authors- Research Scholar Shakti Choudhary, Associate Professor Bhupendra Gupta

Abstract-The study on the cooling effect of attached fins of different geometries on photovoltaic (PV) panels using Computational Fluid Dynamics (CFD) simulation is motivated by the increasing demand for efficient cooling solutions in solar energy systems. This study provides a comprehensive analysis of parametric studies on fins attached to photovoltaic (PV) solar panels, focusing on enhancing their thermal performance and efficiency. The utilization of fins in PV systems is a critical area of research aimed at mitigating the adverse effects of temperature rise on solar panel efficiency. This study use various fin geometries, including rectangular, trapezoidal, and triangular fins, and examines their impact on the thermal regulation of PV panels.

LPG Gas Leakage Detection System

Authors- Ayaan Siddiqui, Dwijesh Y, Faiz Azam, Aditya Wani, Associate Professor Zahid Alam

Abstract-The Gas leakage is one of the big problems with industrial sector, residential milieu and gas functioning vehicles like CNG (Compressed Natural Gas) buses, cars etc. One of the contraceptive methods to stop accidents associated with the gas leakage is to install a gas leakage detection device at vulnerable places. The system detects the leakage of the LPG using a gas sensor and uses the GSM to alert the person about the gas leakage via SMS. When the concentration of LPG in air exceeds a certain level, the sensor senses the gas leakage and the output of the sensor goes LOW. The detection is done by the gas sensor, through the microcontroller the LED and buzzer are turned ON simultaneously.

Experimental Study about Influence of Welding Sequence and Buckling Distortion in Thin-Plate Arc-Welded Joints Using 2 Different Cathodes

Authors- Research Scholar Syed Saif Ali, Assistant Professor Dr. Md Faizan Hasan, Assistant Professor Dr. Mohd Reyaz ur Rahim

Abstract-In the realm of thin-plate arc-welded joints, understanding the influence of welding sequences and the resulting buckling distortion is crucial for optimizing structural integrity and performance. This experimental study investigates the effects of different welding sequences on buckling distortion in thin-plate arc-welded joints. Using two different cathodes, we systematically analyzed the welding-induced distortions to identify optimal welding practices. Our findings reveal that welding sequence significantly impacts the extent and nature of buckling distortion, with specific sequences minimizing distortion and improving joint quality. The comparison of two cathodes provided insights into their performance under varying welding conditions. The study’s outcomes contribute to the development of more effective welding strategies, enhancing the structural reliability of thin-plate welded joints.

A Survey on Digital Text Content Classification Features and Techniques

Authors- Seema Pal, Professor Sumit Sharma

Abstract-There has been a dramatic increase in the volume of documents and texts in recent years. This needs a more refined machine learning techniques for their proper classification in a wide variety of contexts. In the field of natural language processing, many machine learning techniques have performed better than human experts. To be effective, these learning algorithms need to be able to comprehend not only simple models, but also non-linear connections hidden within the data. This study provides an in-depth analysis of the various document categorization methods currently available, allowing for the precise identification of document classes. The importance of preprocessing in text mining for feature creation was also highlighted. The paper contains extensive background research. Concerns unique to the field were also addressed.

A Study on Divdend Policy

Authors- Assistant Professor A.Veeraviswanath, P. Raj Kumar

Abstract-The term dividend refers to that part of the profits of a company which is distributed amongst its shareholders. It may therefore be defined as the return that a shareholder gets from the company, out of its profits, on his share holdings. “According to the Institute of Charted Accounts of India” dividend is a “Distribution to shareholder out of profits or reserves available for this purpose” The Dividend policy has the effect of dividing its net earnings into two Parts: Retained earnings and dividends. The retained earnings provide funds to finance the long¬-term growth. It is the most significant source of financing a firm’s investment in practice. A firm, which intends to pay dividends and also needs funds to finance its investment opportunities, will have to use external sources of finance. Dividend policy of the firm. Thus has its effect on both the long-term financing and the wealth of shareholders. The Moderate view, which asserts that because of the information value of dividends, some dividends should be pa-id as it may have favorable effect on the value of the share.

A Study on Debtors Management

Authors- Assistant Professor M. Nagaraju, K. Subramanyam

Abstract-Debtors are people or businesses who owe you money. Proper management of your debtors will help you get paid faster and prevent bad debts. Prompt collection of debtors’ accounts will also help you maintain a healthy cash flow. Giving your customer an invoice or bill after they have supplied a product or service is a way of offering credit, since you have to wait for the payment. By giving your customers time to pay for goods or services already delivered, you are making it easier for them to make purchases. This will increase sales, but will reduce the cash flow critical to your business.

A Study on Indian Stock Market

Authors- Assistant Professor M. Abdul Basid, S. Khaja Peer

Abstract-With the growth and expansion of the economy, the Indian economy can be considered as a growth engine for the world’s economy. And the stock market of such a quickly growing and developing economy can be considered as the face of the growing markets and companies in it. Stock market represents the secondary market where existing securities (shares and debentures) are traded, stock exchange provides an organized mechanism for purchase and sale of existing securities. By now, we have 24 approved stock exchanges in our country. One of the oldest and fastest stock markets is the Indian stock market platform i.e. Bombay Stock Market (BSE). The stock market or stock exchange is an electronic platform where the shares or securities of different companies can be bought or sold. Another important stock exchange of the country is the National Stock Exchange (NSE). It was incorporated in November, 1992 with an equity capital of Rs. 25 crores. Securities refers to shares, bonds, scrip, stocks, debentures stock and other marketable securities of incorporated companies or similar, government securities. Because of this advanced platform it is now possible for companies to raise capital from public effectively and efficiently. With the current economic reforms in the country, the stock markets have grown exponentially in terms of foreign institutional investment and transaction turnover. This increase is mainly due to the liberalized support along with the regulative role of the government. In India, we have a very low economic literacy rate. This leads to less than 2% of the entire country’s population investing in the stock market.

A Study on Cost Control Techniques

Authors- Assistant Professor A. Veeraviswanath, K. Sirisha

Abstract-In any organization, the major objective is to maximize profit, but the main constraints facing them are the rise in cost of operation. Due to this, the cost of production increases and could lead to certain cost control and cost reduction which make it complex for many organizations to operate as well organized cost limit of knowledge. The study aims to critically examine and evaluate the application of cost control and cost reduction in organizational performance and also to review the budget as an effective tool of cost control and cost reduction. A descriptive survey research was adopted. A total number of 50 questionnaires were administered and used for the study. The analysis of data collected was undertaken by applying appropriate statistical tools. Regression analysis was used to test the hypothesis with the use of SPSS. Based on the findings, it was evident that cost control has a positive impact on organizational performance and also the style of management has a positive impact on organizational performance.

Formulation and Evaluation of Polyherbal Soap

Authors- Mr.Indrajit G. Gore, Mr. Dnyaneshwar P. Gurav, Mr.Avishkar A. Murumkar, Mr.Kiran R. Gore, Assistant Professor Pooja Gaikwad

Abstract-The need to achieve and maintain healthy skin is on the rise. This causes the composition of oxidant detergents with complex synthetic chemicals whose safety on skin and mortal health is still unclear. The present work involved the expression and evaluation of poly herbal detergents. The herbal detergents were formulated using aloe vera, curcuma longa and eclipta alba estimated for colorful parcels like colour, odour, pH, Froth retention, frothheight. Some herbal factory excerpt have antibacterial exertion. The end and ideal of the present study is to formulate antibacterial poly herbal cleaner using eclipta alba excerpt and curcuma longa. The set polyherbal phrasings displayed a good antibacterial effect. The set phrasings were estimated for colorful physicochemical parameters for which good characteristics were observed.

A Survey on Cloud Infrastructure, Attacks and Security Techniques

Authors- Vanshika Jain, Ms. Monika Raghuwanshi

Abstract-With the emergence of artificial intelligence and Big Data initiatives, the imperative for transitioning from traditional analog methods to contemporary solutions like cloud computing becomes increasingly inevitable. Despite the widespread acknowledgment of this necessity in current discourse. This paper has detailed about the requirement of cloud computing and its different services to solve various issues. Further paper has summarized different research work done for the file transfer and its security related models. Paper has list different attacks of cloud with security algorithm for the data transfer.

Enhancing Financial Intelligence: AI Robo-Advisors for Strategic Investment Decisions

Authors- Jeyadev Needhi, Ram Prasath G, Mohamed Riffath K, Manokar S

Abstract-The increasing popularity of Robo-Advisors high- lights the need for sophisticated systems combining big data analytics and deep learning for portfolio optimization. Despite their potential, these AI-driven platforms face notable challenges such as financial data inaccuracies and the risk of overfitting in deep learning models. Overcoming these hurdles requires a concerted effort to enhance reliability and performance. To tackle these challenges effectively, it is imperative to prioritize real-time data integration while minimizing reliance on historical data. By adopting this approach, Robo-Advisors can better adapt to dynamic market conditions, enabling them to provide informed and timely investment recommendations. This proactive stance not only ensures computational efficiency but also fosters investor confidence in the platform’s ability to navigate evolving market dynamics. In conclusion, by continually refining data integration methods and reducing dependencies on historical data, Robo- Advisors can offer more accurate and timely recommendations. This not only enhances the overall investor experience but also upholds ethical standards in automated investment platforms.

Improved Quality of Roadway in Highway Construction and Maintenance Using Soil Mechanics

Authors- Tushar Parashar, Assistant Professor Jitendra Chouhan

Abstract-In this research, it is proposed to stabilize the soil surrounding the water and sewerage networks with sodium chloride to avoid the formation of holes produced by leaks that cause fines dragging that weaken the soil and cause collapse, a phenomenon known as piping or internal erosion. The soil was characterized by the SUCS and AASHTO methods, carrying out the tests of sieving granulometry, sedimentation granulometry, consistency limits, and natural humidity. The compaction test was carried out by means of the modified Proctor test on the standard sample and the samples with the addition of NaCl, to obtain the maximum dry density and humidity, using them as a reference in the unconfined CBR.

Intelligent Transportation and Control Systems Using Data Mining and Machine Learning Techniques

Authors- Prabhat Patel, Dr. Sunil Sugandhi

Abstract-Traffic congestion is becoming the issues of the entire globe. This study aims to explore and review the data mining and machine learning technologies adopted in research and industry to attempt to overcome the direct and indirect traffic issues on humanity and societies. The study’s methodology is to comprehensively review around 165 researches, criticize and categories all these studies into a chronological and understandable category. The study is focusing on the traffic management approaches were depended on data mining and machine learning technologies to detect and predict the traffic only. This study has found that there is no standard traffic management approach that the community of traffic management has agreed on. This study is important to the traffic research communities, traffic software companies and traffic government officials. It has a direct impact on drawing clear path for new traffic management propositions. This study is one of the largest studies with respect to the size of its reviewed articles that were focused on data mining and machine learning. Additionally, this study will draw a general attention to a new traffic management proposition approach.

Casting Defect Reduction in Manufacturing Industry Using Six Sigma

Authors- Scholar Akshay Arzare, Professor Yogesh Ladhe

Abstract-The art of meeting customer specifications, which today is termed as “quality”. Quality is the symbol of human civilization, and with the progress of human civilization, quality control will play an incomparable role in the business. It can be said that if there is no quality control, there is no economic benefit. In the current world of continually increasing global competition, it is imperative for all manufacturing and service organizations to improve the quality of their products. In today highly competitive scenario, the markets are becoming global and economic conditions are changing fast. Customers are more quality conscious and demand for high quality product at competitive prices with product variety and reduced lead time. It is a data-driven quality strategy used to improve processes. Therefore, this paper aims to reduce casting defect in manufacturing industry using six sigma.

Quality Management of Propeller Shaft Using Seven Quality Tools

Authors- Scholar Sourav Choukade, Assistant Professor Vipul Upadhyay

Abstract-Quality, a beacon of human civilization’s advancement, signifies not just the excellence of a product or service, but the very essence of progress itself. As humanity marches forward, propelled by innovation and ingenuity, the significance of quality control in business becomes indisputably profound. Indeed, it can be unequivocally stated: without quality control, economic prosperity remains an elusive dream. In today’s landscape of relentless global competition, manufacturing and service entities alike find themselves at a pivotal juncture. The imperative to enhance the quality of their offerings looms large, casting a shadow over complacency and mediocrity. In this era of heightened consumer discernment and ever-evolving market dynamics, organizations are compelled to embark on a relentless pursuit of perfection. The ethos of quality control permeates every facet of modern enterprise, from meticulous production processes to attentive customer service. It is the cornerstone upon which reputations are built, and the currency through which trust is earned. By embracing quality as a guiding principle, businesses not only meet the demands of today but also lay the groundwork for sustained success in the future.

CFD Analysis of Ejector Use in Refrigeration System

Authors- Scholar Nawed Aqbal Khan, Professor Dr. Ajay Singh, Nitin Barodia

Abstract-The refrigeration system plays an important role in various applications from households to industries. An ejector refrigeration system is one of the thermal driven refrigeration systems. In this study, the performance and optimization of ejectors predicted by the RANS-based CFD model were examined. The effects of primary nozzle throat diameter and primary nozzle discharge diameter were investigated and analyzed to better understand the phenomena inside the ejector. Findings indicate that a critical condenser pressure of 236585 Pa was observed at optimum level of primary nozzle throat diameter of 1.5 and primary nozzle discharge diameter of 9.6. The application of RSM method improves the effectiveness of ejector. Best result is achieved from applying of RSM method.

Implementation of Wavelet Filter for Image Denoising and Analysis of Performance of Parameters

Authors- Scholar Nidhi Verma, Professor Dr Bharti Chourasia

Abstract-During acquisition or transmission, motive noise taints image and video signals. An effective and user-friendly motivating commotion ejection process is therefore necessary. Due to the disturbance, the main exhibition is closed or occasionally there is disappointment. An effective VLSI filter execution with execution upgrade for picture denoising is presented in this paper. The test images vary in size and purpose. The Daubechies 6-tap wavelet filter wavelets are found to beat the approximated denoising execution, which is unbiasedly top sign to commotion proportion and abstractly visual nature of picture. MATLAB and VLSI-Xilinx 14.7 software are used for simulation. The filter architecture will be adjusted with Xilinx version-14.7, and the imaging process will be visualized with MATLAB software.

Improvement Transportation Efficiency Using Modified Clustering Algorithm

Authors- Ankit Shridhar, Assistant Professor Mr. Vinay Deulkar

Abstract-Exploring urban travel patterns can analyze the mobility regularity of residents to provide guidance for urban traffic planning and emergency decision. Clustering methods have been widely applied to explore the hidden information from large-scale trajectory data on travel patterns exploring. How to implement soft constraints in the clustering method and evaluate the effectiveness quantitatively is still a challenge. In this study, we propose an improved trajectory clustering method based on fuzzy density-based spatial clustering of applications with noise to conduct classification on trajectory data. Firstly, we define the trajectory distance which considers the influence of different attributes and determines the corresponding weight coefficients to measure the similarity among trajectories. Secondly, membership degrees and membership functions are designed in the fuzzy clustering method as the extension of the classical method. Finally, trajectory analysis in MATLAB software, india, are divided into two types (workdays and weekends) and then implemented in the experiment to explore different travel patterns.

Mechanical Properties of Quaternary Blended Concrete using Nano Silica

Authors- Professor Dr V Kiran Kumar, Professor Dr T Seshadri Sekhar, Professor Dr P Srinivasa Rao

Abstract-Alternatives to cement as binding material is gaining importance due to increased demand of concrete and since we all know it performs better. We can use the other alternatives to it such as SCMs (supplementary cementitious materials) and also some of these supplementary cementitious materials are byproduct/waste products of other industries. These SCMs will be partially replaced which will imparts higher strength to concrete. The use of SCMs which are in finer in size which densifies the pore structure which leads to increased mechanical and durability properties. This research investigates effect of SCMs like Metakaolin (MK), Flyash (FA) and Nano silica (NS) when used in quaternary blended concrete. In this research, three trial mixes were carried out. For these three trials mixes, the compressive strength is tested at 28 days and it was determined that, for the OPC @60%, MK proportion of 10%, FA @ 30%, and NS @ 3% found to offer the increased strength. For the optimum proportion, casted the samples and compared them with control concrete (only OPC), measured the compressive strength, split tensile strength, and flexural strength as well. 2.29 percent was an observed increase in the compressive strength and 8.4 percent was the increase in split tensile strength. On the other hand the flexural strength was increased by 7.27 percent when the comparison was made with the control concrete. Due to the addition of supplementary cementitious materials this increment is possibly attributed and this leads to the denser and refined micro-structure and also due to the compactness of interfacial zone of transition, we possibly witnessed this increment.

DOI: /10.61463/ijset.vol.12.issue3.183

Vector Machine Learning Models for Human Gesture Recognition

Authors- Pham Quoc Thang, Hoang Thi Lam

Abstract-Human gesture recognition is a complex yet critical task in the field of computer vision, driven by advancements in motion-capture technology and the availability of devices like Microsoft’s Kinect sensor. This paper explores the application of vector machine learning models, specifically Support Vector Machines (SVM), Simplified Support Vector Machines (SimpSVM), and Relevance Vector Machines (RVM), to the problem of human gesture recognition. Our experiments on the Microsoft Research Cambridge-12 Kinect dataset demonstrate that these vector machine learning models achieve high accuracy and competitive performance in gesture classification. SVM and SimpSVM, in particular, exhibit superior accuracy compared to RVM, though RVM shows advantages in classification speed due to fewer support vectors. This study confirms that vector machine learning models are effective for human gesture recognition, providing a promising direction for future research and application in interactive systems.

DOI: /10.61463/ijset.vol.12.issue3.187

Comprehensive Review of Energy-Efficient Region-Based WSN Protocols

Authors- Abhishek Saini, Meenakshi Arora, Rohini Sharma

Abstract-Owing to its many uses in manufacturing automation, healthcare, military inspection, and ecological monitoring, wireless sensor networks (WSNs) have become increasingly popular. To extend network lifetime, energy-efficient procedures must be developed because sensor nodes have limited resources for energy. This is a significant issue. A possible alternative has emerged: region-based protocols, which divide the network into discrete sections to optimize energy use. The present cutting-edge energy-efficient region-based procedures for WSNs are thoroughly examined in this paper. We examine different designs of region-based protocols and highlight how they use data aggregation, hierarchical organizing, and clustering to save energy. The review assesses the energy efficiency, scalability, and resilience of various protocols by classifying them according to their operating approaches. The assessment also discusses the drawbacks and restrictions of current protocols, including their inability to adjust to changing network circumstances, their unequal distribution of energy, and their overhead expenses. Additionally covered are current developments and new directions in region-based WSN protocols, such as cross-layer optimization tactics, adaptive clustering methods, and machine learning algorithms.

Jhum Cultivation in Nagaland: “A Review of Inculpating a Traditional Farming System for Environmental Degradation

Authors- Yasar Sharief, Waheda Mehreen

Abstract-Nagaland is one of the states of India where shifting cultivation or Jhum is considered the predominant way of farming, The Culture of Nagas revolves around Jhum. But in recent times, most people or families who rely on Jhum are turning away from the traditional farming system for many reasons like preferring permanent farming over Jhum, switching to other businesses, migrating to cities/towns, and many more. Some international organizations, researchers, and central and state governments (India) are depicting Jhum as the chief environmental destructing force in Nagaland. Central and state governments are showing alternate ways of livelihood to deviate people from Jhum. The Jhum cultivation has not decreased drastically in Nagaland but fading away slowly the Jhum cultivation area across Nagaland and the number of families who depend on Jhum is not the same as they were at the beginning of the 21st century. Besides the reduction in Jhum cultivation, the environment is degrading rapidly in Nagaland. In this paper, we will analyse a few environmental factors like forest cover, groundwater levels, land desertification, usage of chemical pesticides, and monoculture farming and compare all factors statistically with the Jhum’s presence in the state over the last few years and we discuss the responses related to those factors which we recorded on the ground from farmers, intellectuals of the village and a field assistant of the agriculture department. In the end, we suggested a few steps to preserve the traditional agriculture system and cease the developmental works which are hazardous to the fragile and unique ecosystem of Nagaland.

The Ministry of Power’s Vidhyut Intelligent Chatbot Will Respond to Inquiries about Different Maintenance Procedures within the Substation Using AI

Authors- Assistant Professor Ms. Nitika Kadam

Abstract-Substation Asset Maintenance demands meticulous adherence to standardized procedures across various equipment classes. The complexities inherent in these processes often lead to inefficiencies in query resolution and procedural guidance. This research introduces an innovative solution—an Intelligent Chatbot leveraging Natural Language Processing (NLP)—aimed at revolutionizing the landscape of maintenance assistance. Motivated by the need to streamline maintenance activities and enhance efficiency, this chatbot integrates semantic processing with industrial standards and safety guidelines. Preliminary results showcase promising advancements, illustrating improved query resolution and guided procedural support within substation maintenance workflows. This paper provides an overview of the development, implementation, and initial outcomes of this intelligent chatbot, showcasing its potential to optimize maintenance practices while ensuring compliance with safety protocols and industry standards.

Impact of Labour, Cost of Capital, and Output on the Average Cost of Indian Textile Industry: A Trend Analysis

Authors- Ashita Katiyar, Shivam Kumar Singh

Abstract-The paper determines the average cost function in linear form to examine the cost structure of the textile sector. According to the research, the base level of cost when all other elements are held constant is indicated by the intercept of the linear average cost function, which has a positive value of 0.089 crore and is statistically significant. The average cost and output are found to be significantly inversely correlated by the research, with an output coefficient of -2.53. This indicates that the industry’s economies of scale are highlighted, with an increase in output of one unit leading to a 2.53 unit decrease in average cost. The average cost is also significantly influenced by labour and capital costs. The labour cost has a statistically significant coefficient of 0.0061, whereas the capital cost has a statistically significant coefficient of 0.01598. These coefficients demonstrate how the costs of the textile sector are sensitive to variations in input prices, showing that rises in labour and capital prices result in higher average costs. The strong goodness of fit of the model is demonstrated by an R-square value of 0.914 and a significant F statistic. This high R-square value indicates that differences in labour, capital, and production may account for 91.4% of the variation in the average cost of textiles. Additional research examines the connections among labour cost, capital cost, and production by examining the average cost of the industry. With the goal of helping industry stakeholders maximise production efficiency and cost control, the findings offer a thorough understanding of how these variables interact to affect the textile sector’s entire cost structure.

DOI: /10.61463/ijset.vol.12.issue3.184

Teacher Welfare and Learners’ Performance in Selected Government Aided Primary Schools in Yumbe District, Uganda

Authors- Sebule Nambohe Solomon

Abstract-The study focused on teacher welfare and learner performance in government-aided primary schools in Yumbe District, Uganda. The study was guided by the following objectives: (i) to examine the relationship between teachers’ housing and learners’ performance in government-aided primary schools in Yumbe District; (ii) to assess the relationship between teachers’ provision of meals and learners’ performance in government-aided primary schools in Yumbe District; and (iii) to investigate the relationship between teachers’ administrative support and learners’ performance in government-aided primary schools in Yumbe District. A correlational research design with a mixed research approach was adopted, utilizing both quantitative and qualitative methods. The study population was 240, with a sample size of 148 determined using the Krejcie and Morgan table (1970). Quantitative data was analyzed using SPSS, involving descriptive statistics followed by inferential statistics. The study findings revealed a positive correlation between the provision of meals to teachers and learner performance, with a strong and statistically significant relationship (r = 0.742, p = 0.000). Similarly, administrative support to teachers showed a moderate positive correlation with learner performance, also demonstrating a strong and statistically significant relationship (r = 0.581, p = 0.000). However, the provision of houses to teachers exhibited a weaker correlation with learner performance, which was not statistically significant at the 0.05 level (r = 0.255, p = 0.062). Regression analysis further confirmed significant relationships between teacher welfare factors and learner performance. The provision of meals and administrative support emerged as significant predictors of learner performance, with standardized coefficients (Beta) of 0.11 and 0.20, respectively. For every unit increase in the provision of meals or administrative support to teachers, learner performance was expected to increase by approximately 4.356 units and 4.809 units, respectively. Although the provision of houses to teachers also showed a positive relationship with learner performance, the effect size was relatively smaller (Beta = 0.14, B = 1.214). In conclusion, this study highlights the importance of teacher welfare factors, particularly the provision of meals and administrative support, in enhancing learner performance in primary schools. The study recommends that policymakers and school administrators prioritize interventions that improve teacher welfare, as they have significant implications for overall educational outcomes in government-aided primary schools. Further research should be conducted on the factors influencing teacher welfare and their impact on learner performance, as well as to validate these findings in other contexts.

Radio Coverage Enhancement Techniques

Authors- Sari M Al Handhah, Ahmed F Aklubi

Abstract-This paper explores various techniques used to enhance radio coverage, focusing on recent advancements in technology and methodology. The primary objective is to improve signal strength, reduce interference, and extend coverage areas to ensure better connectivity and user experience. The paper delves into approaches such as Multiple Input Multiple Output (MIMO), beamforming, network densification, and the utilization of advanced software algorithms. Key challenges and future directions in the field are also discussed.

Assessing the Features of the Students in Online Evaluation Systems Using Explainable AI

Authors- Mr. P. Saidhulu, Y.Shamitha, S.Sowmya Sri, U.Nyasa Chowdhary, K.Satish Naidu

Abstract-This paper proposes leveraging Explainable Artificial Intelligence (XAI) techniques to address this issue effectively. By employing these methodologies, such as decision trees, rule-based systems, or local interpretable model-agnostic explanations (LIME), the aim is to not only categorize students based on their behavior and performance but also to provide transparent insights into the decision-making process. Through this approach, educators and administrators can gain a deeper understanding of the factors influencing student engagement, learning patterns, and areas of struggle within the online learning environment. Furthermore, these facilitates the identification of key features and interactions that contribute most significantly to each student profile, enabling personalized interventions and targeted support mechanisms.

A Study on the Significance of Reskilling and Upskilling in Building Employee Value Proposition in IT Companies

Authors- Assistant Professor Rashmi Nair, Assistant Professor Dr. Sheena Abraham

Abstract-Upskilling is undertaking learning to expand the skillset from the existing skillset. Reskilling means learning a totally new skillset from the employee’s existing skillset. The common thing about both is they help the employees to expand their knowledge, but they differ in the end result. With the advent of Industry 4.0 technological disruptions are taking place on a wider scale and Covid-19 has also accelerated the pace of these changes by increasing automation, remote work and flexibility at all levels in IT organizations. The IT companies have witnessed the surge in new technologies such as Artificial Intelligence, cyber security, data visualization, data analytics quantum computing etc. For this skill do a power is required so that the present skills in these organizations do not become obsolete to gain a competitive advantage. So, companies have come up with the idea of Employee value proposition that will motivate the employees to acquire new skills for the benefits and perks they receive in return for the skills, capabilities and experience they bring to the company that helps the company in achieving its goals. When we examine more on the EVP, it is about how the companies wishes to keep themselves unique in terms of motivating people to work and retaining great talents and attracting potential talents in the company by creating a uniqueness in what the company has to offer. As the IT companies are moving towards a technological shift it is important to understand the significance of reskilling and upskilling in building employee value proposition. In this research paper we aim to study the significance of reskilling and upskilling in building employee value proposition in IT companies through descriptive research design for obtaining the objective of the research, a pre-planned and structured questionnaire was used. A sample size of 50 employees from different IT companies were approached on a convenient basis. Both primary and secondary data were used in compiling the study. Secondary data was collected from websites, books and articles while primary data were collected with the help of structured questionnaire from the employees of IT companies.

Integration between Radio and Satellite Phone System

Authors- Ahmad Alotaibi, Hussain Alsalman, Khalid Alhajri, Humoud Alrashidi

Abstract-Reat-time data communication from a point to another point is one of the crucial things for large enterprises especially in the oil and gas fields since they have several plants and rigs in remote areas which requite real-time and reliable communication to ensure that the business and operations are running smooth without any interruption in order to achieve corporate values. The main communication method inside the plants is handheld radio over radio base stations while the main communication method for rigs is utilizing satellite phone over through LEO satellite. Integrating the two systems through establishing direct connectivity between radio servers and satellite phone servers are vulnerable to several major threats that might impact the enterprise operations and security since satellite phone TAE3 encryption. This paper sheds light on a solution that integrate radio and satellite phone system through a box that contains a microcontroller, handheld radio and satellite phone to provide a real-time and reliable communication between plants and rigs. This solution is done by utilizing an intelligent box. The paper highlights the motivation of inventing this solution. After that, the major elements of the intelligent box and its working mechanism will be discussed. Finally, some challenges and difficulties are going to be presented, and then the paper proposes some solutions to overcome such challenges.

DOI: /10.61463/ijset.vol.12.issue3.185

Design and Implimantation of Microstrip Patch Antenna for 5G Communications

Authors- Pratibha Sen, Professor Mukesh Yadav

Abstract-Wireless technology is growing day by day. The antenna plays a very important role in wireless communication. The current mobile communication and wireless technology is working under 4th generation communication, and in the very near future, the technology is switching to 5G communication. The microstrip patch antenna (MPA) design is very useful for small electronics gadgets or communications devices. MPA is light in size, small, and gain-oriented. The practical execution is carried out once the simulation process ends. Before fabrication, the layout of the simulated design is portrayed on Diptrace software, and then by using a photo negative, fabrication is done by the photolithography process. After fabrication, design characteristics are measured using a network analyser. For different frequencies (6.05 GHz, 7.3 GHz, 5.9 GHz, 4.4 GHz, and 5.9 GHz), with maximum gain of 6.74 dBi and bandwidth of 1383 MHz, are obtained. Lastly, in this paper proposed design is compared with previous research papers.

Detection of Intracranial Hemorrhage from CT Scan Using Deep Learning

Authors- Anoop Sai T, Chenreddy Narasimhulu, H vaishnavi,
Naveen R, Assistant Professor Vidyadhar Bendre

Abstract-This study introduces a deep learning model designed to efficiently detect and classify intracranial hemorrhage (ICH) subtypes using non-contrast head CT images. ICH, which involves bleeding within the skull, is a critical condition that necessitates quick and precise diagnosis. The hemorrhages are categorized into intra-axial (intraventricular and intraparenchymal) and extra-axial (subdural, epidural, and subarachnoid) based on their location. Previous computer-aided diagnosis (CAD) systems for ICH detection and classification typically focus on binary classification and have a high number of parameters, leading to increased storage requirements. Moreover, these models often lack the accuracy required for critical medical applications. Therefore, there is a need for a more efficient and accurate automated ICH detection system. To address these limitations, we developed a double- branch model based on the Xception architecture. This model extracts both spatial and temporal features, combines them, and generates a 3D spatial context. These combined features are then fed into a decision tree classifier for final predictions. The dataset for this study was obtained from the 2019 Radiologist Society of North America (RSNA) brain hemorrhage detection challenge. Our model surpassed existing benchmark models, demonstrating higher accuracy rates in detecting various hemorrhage types: intraventricular (96.59%), subarachnoid (96.59%), intraparenchymal (95.36%), and subdural (94.05%), Epidural (99.56%). These results confirm the effectiveness of the proposed double-branch Xception architecture in the detection and classification of ICH.

Compherensive Study on the Impact of Microplastic’s on Wildlife: A Review

Authors- Abhishek Kumar Sharma, Assistant Professor Dr Amrita Lal, Ram Deepak

Abstract-Micro plastics have become one of the most pressing threats to our planet’s biodiversity due to their ubiquitous presence and detrimental effects on wildlife. Micro plastics are microscopic plastic fibres or fragments that can be seen in aquatic and fragile ecosystems like wetlands anywhere from polar to coastal waters. Studies show that micro plastics are ingested by various organisms and cause physical, physiological as well as teratogenic harm even as they may transfer toxins via the food web. The objectives of this research include further insight into the impacts and methods to curb micro plastic pollution on marine life. The purpose of the study is to find knowledge through a detailed analysis of the work done till date as well as through literature review on ecological impacts related to micro plastic and wildlife.

DOI: /10.61463/ijset.vol.12.issue3.186

Enhanced Skin Cancer Diagnosis and Classification Using Convolutional Neural Network Models

Authors- Research Scholar Santara Chouhan, Professor Jitendra Khaire

Abstract-Skin cancer is a prevalent and dangerous condition that poses significant health risks to individuals. Early detection is critical for the effective treatment of skin cancer, as it is for other types of cancer. However, traditional methods of diagnosing skin cancer have demonstrated low accuracy rates and frequently lead to unnecessary examinations. Additionally, many existing machine learning models for cancer detection are limited in the number of skin cancer categories they can identify, which restricts their effectiveness. This research introduces a system that leverages Convolutional Neural Networks (CNNs) to automatically identify skin cancer and benign tumor lesions. The proposed model includes three hidden layers with output channels of 16, 32, and 64, respectively. It operates with a learning rate of 0.001 and employs various optimizers, including Stochastic Gradient Descent (SGD), RMSprop, Adam, and Nadam. Among these, the Adam optimizer delivers the best performance, achieving an accuracy rate of 93% in classifying skin lesions as either benign or malignant, based on the ISIC dataset. The results of this research surpass the accuracy of currently employed skin cancer classification methods. By utilizing the ISIC dataset, the findings demonstrate significant improvements in the detection and classification of skin cancer, offering a more reliable and efficient alternative to traditional diagnostic techniques. programs are essential for minimizing waterborne diseases and enhancing residents’ quality of life.

Research on Lubricating Oil System Used in 300 MW Thermal Power Plant in Viet Nam

Authors- HS Bui

Abstract-The lubricating oil is still used as the main lubricant for all types of machinery. It has become an indispensable and important role for all machinery in general and in the electricity industry in particular. For all types of machinery, when the surface contacts are working, the contact position between the surfaces of the moving parts and the other one move relative to each other will generate frictional forces and wear. In this paper explore the role of lubrification oil for reducing the friction, wear etc. and discussing some case study in 300 MW Thermal power in Viet Nam.

Exploring the Medicinal Potential of Opuntia elatior Mili and Opuntia ficus indica: A Comprehensive Review of Traditional Uses and Scientific Evidence

Authors- Assitant Professor Prajakta Chandrakant Patil

Abstract-The potential of cacti in managing diabetes is one of the findings of the Innovative Review on their therapeutic uses. According to studies, certain of the substances in cacti, especially the prickly pear cactus, may help reduce blood sugar levels by preventing the activation of enzymes that are involved in the digestion of carbohydrates. This may result in the creation of safe and efficient natural diabetic treatments. Folk medicine has long used Opuntia elatior Mili and Opuntia ficus indica, also referred to as nopal or prickly pear cactus. Their therapeutic value is derived from a variety of bioactive components, including vitamins, phenolic compounds, betalains, and flavonoids. The anti-inflammatory, antioxidant, blood-sugar-regulating, digestive-healthy, wound-healing, and weight-management qualities of these plants have all been utilized. Skin diseases, gastritis, and arthritis have all been treated with Opuntia ficus indica and Opuntia elatior Mili’s anti-inflammatory qualities. The plants’ anti-inflammatory properties are partly attributed to the presence of flavonoids and phenolic chemicals in them.. Species of Opuntia have long been used for their hypoglycemic properties and for diabetes management. Prickly pear cactus extract may help control blood sugar levels and enhance insulin sensitivity when taken. For those who already have diabetes or are at risk of getting it, this may be helpful. Additionally, these cacti have historically been used to cure gastrointestinal issues. Indigestion, constipation, and gastric ulcers can all be relieved by the mucilage found in cactus pulp, which has a calming effect on the digestive tract. Additionally, it can support general digestive health and aid in better digestion. For burns and wound healing, the gel that was taken out of the cactus pads has been applied topically. Its calming and antibacterial qualities aid in accelerating the healing process and encouraging skin tissue renewal. The gel can be immediately applied to burns or wounds to aid with pain relief and speed up the healing process. Additionally, it can enhance digestion and support good digestive health in general. Burns and wounds have been treated topically with the gel that was taken from the cactus pads. Its antibacterial and calming qualities hasten the healing process and encourage skin tissue renewal. To assist reduce discomfort and speed up healing, the gel can be put directly to burns or wounds. There may be anti-obesity qualities in Opuntia species. Prickly pear cactus high fiber content can decrease the absorption of dietary fat and promote feelings of fullness. This can assist people in maintaining a healthy weight and supporting weight management initiatives. More investigation is required to completely comprehend the methods of action and possible adverse effects of Opuntia elatior Mili and Opuntia ficus indica, despite their many potential medical applications. Before taking these herbs medicinally, it’s crucial to speak with medical authorities.

Wild Edible Mushroom Use by Tribe’s People of South Gujarat, India: A Review

Authors- Kamgoue Ngamaleu Yves Bertin, Assistant Professor Dr. Prashakha Jyoti Prasad Shukla

Abstract-Food security remains a concern for all countries in the world, edible mushrooms are fungi that can be seen with the naked eye and are relatively easy to gather by hand. Phytochemical and nutritional constituents reveal that they have a capital importance in human and animal nutrition. The preservation of indigenous knowledge, the conservation of biodiversity, the promotion of sustainable practices, the nutritional, medical and economic importance of mushrooms have pushed scientists to become interested in the use of edible wild mushrooms by the tribes of the South Gujarat. Gujarat is one of the states in India with less consumption of edible mushrooms. Also, there is little documentation related to the use of edible mushrooms in the area; The objective of this work is to promote the recognition, utilization, and sustainable management of wild edible mushrooms. The methodology used was the reading of articles and review of previous years. Mushrooms grow in South Gujarat during the rainy season and belong to many families: Agaricaceae, Pleurotaceae, Lyophyllaceae, Tricholomataceae… Wild edible mushrooms are used by local people as source of nutrition, for the exploitation of medicinal properties and as a source of income.

Technological Innovations, Enterpreneurial Innovativeness, and Supply Chain Management of Some Selected Smes in Lagos State. Nigeria

Authors- Dr. Adeniran, Rahmon Tella, Dr. Salau Nurudeen Adeyemi, Professor Adewoye Jonathan Oyerinde

Abstract-The emergence of COVID-19 and other global challenges have compelled Small Medium and Enterprises (SMEs’) globally to be technologically inclined in all their operations, supply chain inclusive, to enhance their development and competitive edge. Thus, the study examined the impact of technological innovation and supply chain management on selected SMEs in Lagos State. The objectives were to determine the relationship between technological innovation variables (i.e. marketing innovation, transportation technology, and information technology) and supply chain efficiency of SMSs in Lagos State and determine to what extent entrepreneurial innovativeness moderates the effect of technological innovations on supply chain efficiency. The sample size was 30 carefully selected SMEs in the manufacturing sector, representing 10 SMEs each from the three senatorial zones in Lagos State., Out of 150 questionees distributed, only one hundred and twenty-three (123) respondents duly completed their instruments, while PPMCC was used to analyse the hypotheses. The study revealed that technological innovations as measured by marketing, transportation, and information technology have a significant relationship with supply chain efficiency as measured by inventory turnover and transportation costs. It also revealed that entrepreneurial innovativeness significantly moderates the relationship between technological innovations and the supply chain efficiency of SMEs. The study concluded that technological innovations are critical to supply chain efficiency. Hence, the study recommended that SMEs adopt all necessary innovations to further improve their supply chain management and invest in robust technological innovation to enhance the supply chain capacity.

DOI: /10.61463/ijset.vol.12.issue3.188

Design and Analysis of Multistory Building and Prediction of its Deflection Using Artificial Intelligence Method

Authors- Deepak Parmar, Associate Professor Rajesh Chouhan

Abstract-On demand of growing population construction of high –rise building is being made compulsory for avoiding land scarcity in future. So these high-rise are difficult to be analyzed manually. So many computerized commercial software are available for analyzing a structure digitally. It uses limit state method in RCC for designing by considering all the standard code books and gives the design. Structural planning and design is an art and science of designing with economy elegance and durable structure. The entire process of structural planning and designing is not only requires imagination and thinking but also sound knowledge of structural engineering besides knowledge of practical aspects such as relevant design codes and by-law backed up by experiences. The purpose of standards is to ensure and enhance the safety, keeping careful balance between economy and safety. The design involves load calculations manually and analyzing the whole structure by STAAD pro and STAAD etc. Complicated and high-rise building need and very time taking and cumbersome calculations using conventional manual methods. STAAD pro provides us a fast, efficient, easy to use accurate platform for analyzing an multi-storey building. Finally we make an attempt to define the economical structure by STAAD.Pro.

Black Friday Sales Prediction Using Machine Learning: An Overview

Authors- Dr. Manju Arora, Shanoor

Abstract-With a major impact on consumer behaviour and sales patterns, Black Friday has emerged as a key event in the retail calendar. Through an analysis of past sales data, economic variables, and consumer emotion, this study seeks to anticipate Black Friday sales. Large online retailers like Amazon, Flipkart, and others entice buyers with sales and discounts across a variety of product categories on Black Friday. This day starts early in the evening, sometimes even a few days in advance, and the stores provide heavily marketed and discounted bargains. This study aims to comprehend, using their demographic data, the purchasing patterns of a varied range of consumers (dependent variable) with respect to different products. Computers can make better decisions because machine learning places a strong emphasis on “learning.” Machine learning models can make more accurate predictions and make better judgments based on past experiences. The philosophy covered in this work aids in the creation of a prediction model that will be very helpful to sales administration on Black Friday.

Innovation Management in the Chemical Industry

Authors- Karri Jaya Naga Akhil Reddy, Karri Shyam Venu Gopala Reddy, Nallamilli Sai Lakshmi, Nallamilli Alekhya Reddy, Nallamilli Swarna

Abstract-This study has been undertaken to explore effective innovation management practices within the chemical sector. The chemical industry, while mature, faces pressure to innovate for sustainability and market demands. We analyze key challenges and opportunities, highlighting the importance of strategic portfolio management and fostering a culture of creativity. By examining successful approaches, the paper aims to contribute valuable insights for enhancing innovation capabilities in the chemical industry.

A Land Cover Classification Using a Random Forest Model

Authors- Davaasuren Bayarmagnai, Professor Bayanjargal Darkhijav, Professor Tsolmon Renchin

Abstract-Earth’s surface forms the outermost layer of our planet, and it changes due to both natural processes and human activities. Therefore, the classification of land surface features is essential for many environmental applications and serves as the basis for survey studies. Various methods are used for land cover classification using satellite data, such as random forest classification and the decision tree method of machine learning. In this study, we used the Random forest(RF) classification, which shows robustness and provides high accuracy compared to other image classification methods in remote sensing. The study area is in Khangal soum of Bulgan province of Mongolia, a forest-steppe zone with mountains and hills. Land cover types of the study area include bare land, forest, and grass. Spectral bands of Blue, Green, Red, and Near Infrared(NIR) of Landsat 8 data and ground observation data were used in the research. A confusion matrix was obtained by comparing the results obtained by the random forest method with the ground observation values, and the result was 86.4 percent. Using the results, we applied Random forest results to create a land cover map for 2017-2021. However, larch forests are estimated to be the most significant percentage in the study area. RF can be applied to different forest classifications in any forested region of Mongolia to save time and money.

DOI: /10.61463/ijset.vol.12.issue3.189

Automatic Enemy and Metal Detecting Defense Robot by Using Wireless Technology

Authors- Associate Professor Bomma Satya Prasad, Assistant Professor Challagulla Purnaprakash, Beerelli Laxmi Mamatha, Repaka Sanjana, Thatikayala Swetha

Abstract-In this project we are going to design an automatic defence robot with enemy (human) detection using face detection technique by blending in the power of Arduino and Android. the mobile camera will move along with enemy face with the help of servos. The advantage of using the Android Mobile Phone here is that you do not need to invest on a camera module and the whole image detection work can be done in the phone itself; you do not need your Arduino connected to your computer for this to work. Here we have used Bluetooth Module with Arduino to communicate with Mobile wirelessly. A land mine is an explosive device concealed under or on the ground and designed to destroy or disable enemy targets, ranging from combatants to vehicles and tanks, as they pass over or near it. Such a device is typically detonated automatically by way of pressure when a target steps on it or drives over it, although other detonation mechanisms are used. A land mine may cause damage by direct blast effect, by fragments that are thrown by the blast, or by both. The name originates from the ancient practice of military mining, where tunnels were dug under enemy fortifications or troop formations.

Integrated Energy Management Strategy for Grid-Connected DC Microgrid

Authors- Associate Professor Dharavath Upender Naik, Assistant Professor P. Naga Brahmmam, Velpula Ravindra, Gattipally Navya, Varsa Anil

Abstract-According to the unpredictable behavior of renewable energy sources and load demand, energy management in DC microgrids is difficult and complex. Balancing power converter regulation processes, peak demand and lack power are some of the main issues. For the DC microgrid to operate reliably and effectively, great care must be taken in how the photovoltaic (PV) system and battery energy storage system (BESS) are used. For the purpose of resolving the preceding issues, this paper proposes employing the DC microgrids centralized energy management approach. Coordinating between the DC microgrids intellectual layer and several electrical surface parts is the CEMS. To control energy during peak and off-peak load demand, optimize PV-BESS consumption and carry out load dropping operations, it makes use of multi-optimization. In order to prevent overusing AC grid power, a suitable approach to the PV-BESS problem is also developed and addressed via linear programming. In cases of PV power deficiency, the best way to implement load splitting is to solve a mixed-integer linear programming problem in order to maintain power balance and DC bus voltage management. The PV systems efficient functioning in maximum power point tracking, OFF-MPPT mode (i.e., voltage regulation), and BESS charging and discharging are all shown by the proposed CEMS. It is demonstrated that the DC microgrid operations performance, efficiency and availability are enhanced by the hierarchical control structure of CEMS. Therefore, a 48V and 1.2-kW PV-BESS-based DC microgrid system is built in MATLAB/Simulink to demonstrate the effectiveness of the proposed method under various conditions.

Enhancing Pervious Concrete Pavement

Authors- Associate Professor Gugulothu Nagesh, Associate Professor Kashimalla Ravindra

Abstract-When it comes to transportation, road infrastructure is essential for promoting connectivity and mobility. However, because of things like subgrade soil conditions, building materials, and construction techniques, the strength and endurance of traditional pavements have come under more and more criticism. A sustainable solution to these problems that can manage stormwater and ease the problems associated with standing water on road surfaces is the idea of pervious concrete pavement, or PCP. The goal of this proposed project is to add admixtures to PCP to increase its strength and durability. To maximize pavement performance, critical components of Portland cement pavement (PCP), such as cement, coarse aggregate, water, and additives like fly ash and ground granulated blast furnace slag (GGBS), are carefully analyzed.

Intelligent Edge-Based Driver Fatigue Identification in Mobile Crowdsourcing

Authors- Assistant Professor U. Vara Prasad, Assistant Professor B. Srinivas, K. Bharath Nag, J. Anusha, S. Sushma, V. Sunil Kumar, S. Ravindhar Reddy

Abstract-Drowsy drivers pose a serious risk to public safety through their involvement in traffic accidents. According to recent data, drunk drivers are thought to be responsible for 15.5% of fatal collisions. A sleepiness detection system can help prevent these incidents a great deal, especially with the increasing usage of roadside units and mobile devices. Although a number of solutions have been put out in the literature, none of them fully presents a distributed architecture that can satisfy these applications’ requirements without invading the privacy of the drivers. In this research, a smart edge computing-based two-stage driver drowsiness detection system is proposed. Without disclosing their personal information, mobile devices in the vehicle are utilized to record and evaluate the drivers’ present states. When sleepiness is verified, the smart edge is used as a decision-maker.

Consequences Due to Transmutation of Agriculture Land to Aquaculture Land Using Gee

Authors- Associate Professor Gugulothu Nagesh, Associate Professor Kashimalla Ravindra, Gudipuidi. Sathya Sai, Mohammad. Yaseen, Maloth. Tharun

Abstract-The transmutation of agriculture land to aquaculture land has become a critical environmental and economic concern. This project employs Geographic Information System(GIS) technology, specifically Google Earth Engine(GEE), to assess the consequences of the land-use transformation key factors addressed in this research are utilized to analyze and visualize the spatial dynamics of this transition. The findings of this study aim to provide valuable insights for sustainable land-use planning and policy development in the context of the growing aquaculture industry and its implications for agriculture and ecosystem. The research examines the environmental, economic, and social consequences of this land- use transition. Through spatial analysis and data modeling, the study aims to provide insights into the potential benefits and drawbacks of such transmutations, offering valuable information for policymakers, land managers, and stakeholders in the realm of agriculture and aquaculture. The conversion of agricultural land to aquaculture land refers to the transformation of arable land traditionally used for crop cultivation or livestock farming into facilities dedicated to the cultivation of aquatic organisms. This shift involves the creation of ponds, tanks, or other aquatic enclosures for the purpose of raising fish, shellfish, or aquatic plants. This abstract will explore the reasons for such conversions, their environmental and economic implications, and the challenges associated with this transition.

Dynamic Analysis on High-Speed Electrical Machines

Authors- Assistant Professor Bakka Pushpa

Abstract-This paper centers around rotor dynamic investigation of the attractive levitation based fast electrical machine First and foremost, the powerful model of the attractive levitation rotor is laid out and the help solidness of the attractive heading is determined. Moreover, the rotor framework’s dynamic investigation with ANSYS programming is carried out with the supposition that attractive bearing is considered as a specific firmness of spring model. Finally, the critical speeds and vibration modes of the rotor system are uncovered. In addition to providing theoretical support for the safe operation of the rotor system, the analytical result also contains the global stiffness and mass matrix coefficients [M] and [K], the damping matrix coefficient [C], and the external force vector [F(t)]. In the event that there is no outer power, it is free vibration condition and {F(t)}=0. The damping effect can be ignored when calculating natural frequencies and modes for free vibration. As a result, the free vibration equation will be simplified in the following manner: by utilizing lower-order critical speed control, but it will also serve as an important reference for the rotor’s structure design and optimization.

Electric Vehicle Battery Charging System with Solar PV system and PID Controller

Authors- Assistant Professor R. Kathiresan, Sugapriya.K, Nishanth.P, Snehapriya.M

Abstract-As infrastructure advances rapidly across the globe, the need for electricity has grown significantly. Among the potential renewable energy resources available, photovoltaics (PV) is a particularly alluring choice. By expanding the use of PV systems, it is possible to fulfil the required energy demands. To extract the maximum power from PV modules, the maximum power point tracking (MPPT) technique is implemented. The Perturb and Observe MPPT algorithm is employed to track the peak power point of the photovoltaic panel, even under fluctuating solar irradiance conditions. A battery charge controller is also utilized to monitor the battery’s state of charge (SOC) and voltage levels. Additionally, a DC-DC boost converter has been designed and integrated with the PV model to validate the PV module’s performance as a power source. The simulation results with the DC-DC boost converter, both with and without the PID controller model, show its effectiveness in increasing the input voltage to the necessary level for charging electric vehicle (EV) batteries.

Exploring a New Dimension of Lippan Art: the Mahabodhi Temple Embellished With Tie and Dye Work

Authors- Assistant Professor Dr. Deep Shikha Pandey, Ms Shweta Kumari

Abstract-Lippan art is a traditional form of mural art that originates from the Kutch region of Gujarat, India historically the inhabitants of this region decorated their homes with intricate designs using clay and adorned them with small Mirrors to create shimmering effects. Today Lippan art is not only used for decorating walls but also for creating standalone pieces such as frames, panels and other decorative items. This approach not only show case the versatility and adaptability of Lippan art but also exemplifies how traditional art forms can be revitalized and given new relevance in contemporary setting. By merging Lippan art with Mahabodhi Tample, research work highlighted the potential for traditional crafts to penetrate new markets and find a place in modern homes and businesses. The use of Tie and Dye another traditional craft in conjunction with Lippan Art, further emphasizes the richness of cultural heritage and its application in creating unique, cross cultural, artistic expressions. This innovative application demonstrates how traditional arts can be transformed to meet contemporary tastes and commercial needs, of opening up new opportunities for artisans and promoting cultural heritage in the Morden work.

Generalized Lauricella Function & Fractional differential operators involving Multivariable H – Function

Authors- Ram Niwas Meghwal, Dr. K.G. Bhadana

Abstract-In this paper we use fractional differential operators and to derive a number of key formulas of multivariable H-function. We use the generalized Leibnitz’s rule for fractional derivatives in order to obtain one of the aforementioned formulas, which involve a product of two multivariables H-function. It is further shown that ,each of these formulas yield interesting new formulas for certain multivariable hypergeometric function such as generalized Lauricella function (Srivastava-Dauost)and Lauriella hypergeometric function some of these application of the key formulas provide potentially useful generalization of known result in the theory of fractional calculus.

A Study on the Application of Financial Analytics in the Field of Blockchain Technology

Authors- Professor Dr.K.Baranidharan, Research Scholar K. Sabitha, Research Scholar V. Deepika

Abstract-An important new field of research at the crossroads of blockchain and distributed ledger technologies is financial analytics. The potential uses, difficulties, and consequences of financial analytics in blockchain environments are investigated in this research. Examining how stakeholders and financial institutions use the immutable ledger of blockchain technology to better monitor transactions, optimize risk management techniques, and make better decisions is the focus of the project. Regulatory factors influencing blockchain adoption, the influence of decentralized finance (DeFi) on financial analytics, and the incorporation of AI and ML algorithms for predictive modeling are important subjects. Insights into future research paths and practical consequences for financial institutions navigating the digital economy are offered by this study, which synthesizes current literature and empirical findings to contribute to understanding the transformative potential of financial analytics in blockchain.

DOI: /10.61463/ijset.vol.12.issue3.190

Analytical Examination of Dynamic Quick Response Codes in Vaccine Cold Chain Logistics

Authors- Wanzi

Abstract-Ensuring the integrity of temperature-sensitive vaccines during distribution is paramount for maintaining their efficacy. Cold chain logistics, a crucial aspect of vaccine distribution, requires precise temperature control to prevent degradation. This experimental case study examines the implementation and effectiveness of Dynamic Quick Response (QR) codes integrated with temperature sensors and data loggers in cold chain monitoring. Findings from the study indicate that dynamic QR codes provide robust and reliable solutions for cold chain logistics. The continuous tracking and real-time data transmission capabilities ensure immediate access to critical temperature information, enabling rapid corrective actions. The results underscore the significant benefits of dynamic QR codes in enhancing cold chain monitoring, ensuring vaccine potency, and preventing spoilage. The study supports broader adoption of dynamic QR codes in vaccine distribution, addressing the challenges of maintaining temperature integrity in cold chains and ultimately safeguarding public health.

A Study on E-HRM: A Review and Implications

Authors- Assistant Professor Dr. Atul Kumar, Assistant Professor Asha, Assistant Professor Nutan Singhwal

Abstract-The latest management based on information technology has appeared to improve communication and information technology. Because it is easy to access them, HRM’s decision-making support system is more effective, successful, creative and capable in promoting strategic goals and developing new E-HRM strategies. Most recent developments in HR have been significantly impacted by technology. Most recent developments in HR have been significantly impacted by technology which focuses on information-based relevant data, self-service, and interactive workplace. Advances in technology require strategic HRM to adapt to changing employee attitudes, become more adaptable, and become more cost-effective. It is therefore important to assess the positive and negative impacts when implementing and developing E-HRM. This article reviews current empirical research on electronic human resource management (e-HRM) and discusses implications for future research. Based on a definition and initial structure, the review analyzes the theories used, the empirical methods used, the level of analysis chosen, the topics investigated, and the results identified. The review uncovered an initial body of research from multiple disciplines that was primarily non-theoretical, used a range of empirical methods, and addressed multiple levels of analysis and a variety of core e-HRM topics. Based on the review, some initial theoretical, methodological and thematic implications are discussed to support a future e-HRM research agenda.

DOI: /10.61463/ijset.vol.12.issue3.630

Indian IT Department: Moon Light Review

Authors- Assistant Professor Nishi Thakur, Assistant Professor Atul Kumar, Assistant Professor Nutan Singhwal

Abstract-Gig work, or moonlighting, has grown significantly over the years, and Covid has exacerbated this trend. Moonlighting is the phenomenon where people work outside of their regular work hours for another organization full-time, contract, or freelance. Having worked in several organizations to solve various problems such as boredom, Additional funding, etc. is becoming more common and is most likely done by the younger generation of employees. Moonlight increases withdrawal behaviour, causing them to avoid and from their separation behaviourIn the workplace, employees are more focused on establishing self -identification than the team, which has led to various others question.Some people pursue their hobbies in their free time while others are looking for part -time jobs. Especially in her IT industry, employees worked her two jobs at the same time and leveraged the remote working model. The idea of working for two organizations is termed moonlighting. This case study covers various aspects and impacts of moonlighting in the Indian IT industry including pre- and post-Covid situations to IT company’s stand andfuture of work.

DOI: /10.61463/ijset.vol.12.issue3.631

The Impact of Association on Supply Chain Efficiency

Authors- Assistant Professor Ms. Anika, Ms. Zeba Tahir, Mr. Abhishek Kumar

Abstract-In today’s global business environment, with rapidly changing technologies, intense competition, increased emphasis on outsourcing, creation of value-added products for the consumers, and the growth of highly specialized companies; it is increasingly important that companies within the supply chain collaborate. However, collaboration is a complex process that does not always lead to success – if not adopted in a right manner. Collaboration, in this study, refers to the combination of efforts within and between the organizations (internally as well as externally) to utilize their resources in the most efficient manner (instead of replicating them) and thereby to develop and create dynamic capabilities and mutual benefits for all participating firms. This enhanced relationship also brings new innovations to the participating firms in the form of new and improved products, reduced costs, reduced lead time, better customer services, development of trust, commitment between the organizations and enhancement of performance in the overall supply chain. The research paper focus on the aspect of collaboration, the need for new competencies to the organizations and the relevance of collaboration to enhance cross-organizational capabilities. The study aims to find out why most of the organizations want to collaborate instead of competing in the market? Why they want to share their ‘Bigger Pie’ with others instead of accepting their own ‘Pie’ from the market? And finally, how does the collaboration enhance cross-organizational capabilities?

DOI: /10.61463/ijset.vol.12.issue3.632