| 1 |
Author(s):
Dr. Ranjith Somasundaran Chakkambath; Devi Priya; Shiwangi Mishra.
Page No :
|
The Impact of AI and Automation on Job Opportunities for Job Aspirants: A Perspective
Abstract
Artificial Intelligence (AI) and automation are rapidly transforming the job market, raising concerns among job aspirants about employment prospects. This study explores the perception of fresh graduates and students currently pursuing higher education regarding AI's impact on job opportunities. Using a descriptive research design and convenience sampling, the study focuses on graduates and postgraduates from various disciplines in Ernakulam district. The research aims to assess the awareness, concerns, and preparedness of job seekers in adapting to AI-driven changes in hiring processes and employment trends. Findings will provide insights into whether aspirants view AI as a threat or opportunity, their confidence in securing jobs, and the importance of reskilling and upskilling to remain competitive. The study also examines the role of universities and employers in preparing students for AI-driven industries. The results will help policymakers and educators develop strategies to support graduates in an evolving job market.
| 2 |
Author(s):
PAVAN TK.
Page No :
|
AI-Based Classification of Bacterial Biofilm Formation via Time-Lapse Microscopy
Abstract
Bacterial biofilms, which are microbial communities embedded in extracellular matrices, contribute to various chronic infections and pose significant challenges in both medical and industrial settings. The formation of biofilms is a dynamic and complex process that can be difficult to study using traditional methods. Time-lapse microscopy provides a valuable tool for observing biofilm development over time, but analyzing the resulting images manually is labor-intensive and prone to error. Recently, artificial intelligence (AI), particularly deep learning models, has emerged as a promising solution to automate the classification of biofilm formation from time-lapse microscopy data. These AI models can classify different stages of biofilm growth, such as initial attachment, microcolony formation, maturation, and dispersion, and also quantify important biofilm characteristics like size, density, and structure. This paper examines the application of AI in classifying bacterial biofilm formation, highlighting the benefits and challenges of implementing these techniques in research and clinical settings.
| 3 |
Author(s):
Navyashree.
Page No :
|
The Use of recent Large Language Models (LLMs) for Literature Mining of Emerging Zoonotic Pathogens
Abstract
The identification and understanding of emerging zoonotic pathogens are critical to preventing pandemics and managing public health risks. Traditional pathogen discovery and epidemiological surveillance methods are dependent on manual literature reviews, which can be inefficient and inadequate given the sheer volume of scientific literature. Large Language Models (LLMs) present a promising solution for automating the process of literature mining, enabling rapid identification and understanding of zoonotic pathogens. These AI models can process vast amounts of text, extract relevant insights, and generate hypotheses about the ecological, genetic, and epidemiological traits of zoonotic diseases. This paper explores how LLMs can be employed to enhance the study of emerging zoonotic pathogens, focusing on their capabilities, applications, challenges, and potential future directions.
| 4 |
Author(s):
Bhavana Dhoundiyal and Swati Bhati.
Page No : 1-2
|
ONLINE DISPUTE RESOLUTION
Abstract
ONLINE DISPUTE RESOLUTION
| 5 |
Author(s):
Khushi Agrawal.
Page No : 1-3
|
INTERN-SHALA AUTOMATION: STREAMLINING INTERNSHIP APPLICATIONS THROUGH INTELLIGENT SCRIPTING
Abstract
The process of applying for internships
on platforms like Intern-shala is often timeconsuming, repetitive, and prone to human error,
especially for students managing multiple
applications. This paper introduces Intern-shala Automation, a Python-based solution designed to streamline the internship application workflow. The tool leverages browser automation techniques using Selenium to auto-fill and submit internship
applications based on user-defined preferences such as location, duration, and skill requirements. This project not only enhances efficiency and accuracy but also frees students from the monotony of manual submissions, enabling them to focus more on preparation and learning. The paper outlines the problem statement, proposed solution architecture, implementation, and performance outcomes. Future scope and ethical considerations are also discussed.
| 6 |
Author(s):
MOHAMMED MOHSIN .
Page No : 1-3
|
Best Practices Lessons Learned – IICS Implementation IADB
Abstract
Communicates technical workings of data, fosters the goal of data re-use, and designs policies and processes to improve the underlying integrity of information to the organization. Responsible for uploading and curating catalog assets.
| 7 |
Author(s):
PRINCE.
Page No : 1-3
|
Does Planting Trees Really Fight Climate Change?
Abstract
Tree planting has emerged as a widely promoted strategy for mitigating climate change, often portrayed as a
natural solution for capturing atmospheric carbon dioxide. This research paper critically examines the extent
to which afforestation and reforestation efforts contribute to combating climate change. Drawing on recent
scientific findings, global carbon sequestration data, and satellite monitoring advancements, the study
explores both the potential benefits and limitations of tree planting as a climate mitigation tool. While trees
do absorb and store significant amounts of CO₂, the overall impact varies greatly depending on species
selection, geographic location, biodiversity considerations, and the longevity of carbon storage. Moreover,
the paper highlights ecological risks such as soil carbon loss, biodiversity disruption, and albedo changes
that may counteract climate gains if tree planting is poorly planned. The research concludes that while
planting trees can play a valuable role in climate action, it must be integrated with broader strategies
including emissions reduction, forest protection, and ecosystem restoration to be truly effective. Strategic,
science-based implementation is essential to ensure that reforestation efforts deliver genuine and lasting
climate benefits.
| 8 |
Author(s):
Dr.S.Jeyalakshmi, Ms.Shivani Rajendran.
Page No : 1-3
|
LGBTQ+ Inclusion as a Strategy for Company Growth: A Roadmap for Organizational Success
Abstract
LGBTQ+ inclusion in the corporate environment has rapidly become an essential factor in business success. With diverse stakeholders, changing societal values, and a new generation of employees and consumers who prioritize inclusivity, companies that integrate LGBTQ+ inclusion into their strategy are more likely to experience sustained growth. This paper examines the business case for LGBTQ+ inclusion, its impact on corporate performance, and provides a practical framework that organizations can implement to ensure a supportive, diverse, and innovative work environment. Furthermore, it identifies the challenges that companies may face in this journey and suggests mitigation strategies to achieve a comprehensive inclusivity model.
| 9 |
Author(s):
Rajeev Ranjan.
Page No : 1-3
|
AI-Driven Discovery of Nanomaterial Synergies for Next-Generation Antibiotic Alternatives
Abstract
The global rise of antimicrobial resistance (AMR) has necessitated the urgent development of alternative therapeutic strategies to combat resistant pathogens. Nanomaterials have gained significant attention due to their intrinsic antimicrobial properties and potential to disrupt microbial structures, offering a promising avenue for the development of next-generation antibiotics. However, the vast combinatorial possibilities of nanomaterial properties, such as size, shape, surface charge, and functionalization, present a significant challenge in identifying optimal synergies that maximize antimicrobial efficacy while minimizing toxicity. Artificial intelligence (AI), particularly machine learning (ML), provides a powerful tool to address this challenge by enabling the systematic discovery and optimization of nanomaterial combinations. By analyzing high-dimensional datasets, AI can predict synergistic combinations of nanomaterials with enhanced bactericidal activity and reduced cytotoxicity. Furthermore, generative AI models, including variational autoencoders and generative adversarial networks, facilitate the de novo design of novel nanomaterial structures with desired antimicrobial properties. AI also plays a critical role in elucidating the mechanisms underlying nanomaterial-microbe interactions, providing insights into the molecular pathways involved in microbial resistance and guiding the design of nanomaterials that minimize resistance development. Despite the promising potential of AI in nanomaterial synergy discovery, challenges such as the quality and diversity of training datasets, model interpretability, and data standardization must be addressed. Collaborative efforts across computational, microbiological, and clinical disciplines are essential to translate AI-driven nanomaterial discoveries into clinically viable antibiotic alternatives for combating AMR.
| 10 |
Author(s):
Yogesh and Sandhya.
Page No : 1-3
|
Machine Learning Approaches to Engineer Nanoantibiotics for Treating Infections in Immunocompromised Patients
Abstract
The rising prevalence of drug-resistant infections among immunocompromised individuals, including organ transplant recipients, cancer patients undergoing chemotherapy, and individuals with immune deficiencies, presents a growing challenge in modern medicine. These patients are particularly susceptible to infections that do not respond to traditional antibiotics. Nanoantibiotics, which are nanoscale materials with antimicrobial properties or serve as delivery systems for antibiotics, offer promising therapeutic alternatives. However, designing and optimizing these nanoantibiotics require meticulous control over various parameters, such as particle size, shape, surface functionalization, and drug loading. Machine learning has emerged as a transformative tool in accelerating the development of nanoantibiotics by enabling the predictive modeling of complex biological and physicochemical interactions. Machine learning algorithms can analyze large datasets from laboratory and clinical studies to predict antibacterial potency, toxicity, stability, and drug release profiles, thereby streamlining the design process. Additionally, machine learning can assist in optimizing nanoparticle configurations, improving the balance between antimicrobial effectiveness and minimal toxicity to human cells. While challenges such as model interpretability and data quality remain, the integration of machine learning into nanoantibiotic development has the potential to revolutionize personalized treatments for immunocompromised patients, providing safer, more efficient therapeutic options.
| 11 |
Author(s):
Anurag Gautam, Devendra Singh, Anita Pandey, Vipin Singh .
Page No : 1-4
|
Design of a Solar Tracking System for Renewable Energy
Abstract
In this study, a solar tracking system for renewable energy applications is developed and constructed to harness free solar energy, store it in a battery, and convert it into alternating current (AC) for household use. The system can serve as a supplementary or standalone power source for standard homes. It is engineered to react quickly to environmental changes. Potential errors, whether in hardware or software, are minimized through extensive testing, quality assurance practices, and are further managed with redundancy and error detection algorithms. The system undergoes thorough testing to ensure real-time responsiveness, reliability, stability, and safety. It is built to maintain stability during operation and withstand weather conditions, temperature fluctuations, and minor mechanical stresses. Additionally, it features fail-safe mechanisms, enabling it to recover from faults or alert users when failures occur.
| 12 |
Author(s):
B. Priyadharshini .
Page No : 1-4
|
A Study on Algebra’s Crucial Role in Everyday Life
Abstract
Algebra plays a pivotal role in everyday life, extending for beyond the
confines of academic study. This abstract explores how algebraic principles
underpin various practical activities and decision-making processes. From
budgeting personal finances and managing household expenses to optimizing time
management problem-solving in professional settings, algebra provides a
structured approached to understanding and organizing complex information. The
abstract delves into specific examples such as calculating interest rates, analyzing
data trends, and modeling real-world scenarios. By highlighting these applications,
the discussion underscores algebra's significance as a fundamental tool for critical thinking and practical problem-solving in diverse contexts.
| 13 |
Author(s):
GAMPALA SUMAN.
Page No : 1-4
|
DEEP-LEARNING BASED FUNDUS ANALYSIS FOR EARLY DETECTION AND MANAGEMENT OF DIABETIC RETINOPATHY
Abstract
Diabetic retinopathy (DR) is a progressive condition that can cause vision loss. It starts out subtly and gets worse with time. It affects approximately 35% of people with diabetes worldwide. According to research, a new case of diabetic retinopathy is diagnosed every few minutes. In its early stages, retinal images are frequently difficult to recognize due to their complexity. In the area of medical imaging, Deep Learning is growing. Convolutional Neural Networks (CNN) and other architectures are used in this study to see how they can be used to accurately detect and classify the stages of diabetic retinopathy. Our approach utilizes publicly available datasets and several deep learning techniques are used to identify and categories the Fundus images into four stages of DR will be compared in this work. Model robustness is enhanced using data preprocessing methods like normalization, augmentation, and segmentation. The models are evaluated using performance metrics like accuracy, precision, recall, F1-score, and Area Under Curve (AUC). The results demonstrate that deep learning models can achieve high classification accuracy, outperforming traditional machine learning methods. Ophthalmologists may find it easier to comprehend model predictions if they are able to gain insight into the regions of interest that are essential for decision-making through visual interpretation of the models. This study underscores the potential of deep learning to revolutionize diabetic retinopathy diagnosis, offering a foundation for future research in integrating multi-modal data and real-world applications.
| 14 |
Author(s):
Babu Rajendra.
Page No : 1-4
|
AI in Preventive Psychology: Predicting Mental Health Crises Using Behavioral and Social Data
Abstract
Artificial Intelligence (AI) has become a powerful tool in the realm of mental health, particularly in the prevention of mental health crises. By leveraging predictive analytics, AI systems can analyze behavioral and social data to identify early warning signs of mental health issues before they escalate into full-blown crises. This paper explores the potential of AI in preventive psychology, focusing on its ability to predict and mitigate mental health crises. It examines the types of behavioral and social data that AI systems utilize, the machine learning algorithms that power these predictive models, and the ethical implications surrounding the use of AI in mental health care. Through a review of current research and applications, the paper also highlights the benefits and challenges associated with the use of AI in early mental health intervention.
| 15 |
Author(s):
Ms G. Monica Gladys .
Page No : 1-4
|
A ROLE OF MATRICES IN MEDICAL APPLICATIONS
Abstract
Matrices are fundamental tools various domains, providing a versatile framework for representing,
analyzing data and transformation. This paper explores the application of matrix across the different
field emphasizing their role in medical by providing how matrices are utilized to solving the system.
This paper examines matrix and its application. This paper work also goes further to apply matrix to
solve a 2×2 disease spread model. In essence a matrix is a rectangular array of numbers or other
mathematical objects, which can be used to represent and manipulate data systemically. The application
of matrix has revolutionized the way data is handled and analyzed in the domains, offering a structured
approach to solving complex problems. In the medical field, matrix is instrumental in managing and
analyzing the large volumes of patient data.
Matrix theory, particularly through the use of transition matrices offers valuable insights into the
dynamics of disease spread in medical.
| 16 |
Author(s):
Satish.
Page No : 1-4
|
Early Infection Detection Through AI Analysis of Host-Microbiome Interactions
Abstract
The early detection of infections is a critical challenge in modern medicine, as timely intervention is key to preventing disease progression and complications. Traditional diagnostic approaches, which focus on identifying specific pathogens, can sometimes be slow and are not always effective in detecting infections in their early stages. Advances in artificial intelligence (AI) and microbiome research offer a promising solution for improving early infection detection. The microbiome, a complex community of microorganisms residing within and on the human body, plays a pivotal role in maintaining health and influencing disease outcomes. When disrupted, the balance of the microbiome, referred to as dysbiosis, can signal the onset of various infectious diseases. AI techniques can analyze host-microbiome interactions to identify early biomarkers of infection, even before clinical symptoms appear. This article explores how AI is being used to analyze microbiome data for early infection detection, discusses the potential applications, and addresses the challenges and opportunities in this field.
| 17 |
Author(s):
Bindhushree.
Page No : 1-4
|
Deep Learning for Antimicrobial Resistance Prediction from Bacterial Genomes
Abstract
Antimicrobial resistance (AMR) is rapidly becoming one of the most significant challenges in modern medicine, complicating the treatment of bacterial infections. As pathogens evolve resistance to multiple classes of antibiotics, early detection and prediction of AMR have become critical. Traditional methods for identifying antimicrobial resistance are often slow and labor-intensive. However, deep learning (DL) methods, particularly those that analyze genomic data, have shown great promise in improving the speed and accuracy of AMR predictions. By leveraging bacterial genomic sequences, deep learning models can predict resistance patterns and provide insights into the genetic underpinnings of AMR. This article explores the application of deep learning techniques in the prediction of AMR from bacterial genomes, emphasizing the advantages and challenges of these methods. It also highlights the potential future directions for integrating deep learning with genomic technologies to improve the detection, management, and treatment of antimicrobial-resistant infections.
| 18 |
Author(s):
Darshan H B, Mallikarjuna D M, Shivaningappa Teli, Suma M R, Vidyashree K N .
Page No : 1-4
|
REVIEW ON EMS INDUSTRY PROCESS FLOW
Abstract
The Surface Mount Technology (SMT) industry is a cornerstone of modern electronics manufacturing, offering high component density, improved performance, and reduced production costs. However, ensuring optimal workflow in SMT lines remains a complex challenge due to the interplay of process variables across multiple stages—printing, placement, reflow, and inspection. This paper presents a comprehensive SMT industry workflow framework, integrating proven defect minimization strategies from no-clean solder processes with contemporary best practices in smart manufacturing. By analysing key defects such as solder balling, tombstoning, bridging, and skewed components, the study outlines root causes and preventive techniques drawn from real-world production data and empirical research. Special attention is given to reflow profiling, environmental control, and material handling as critical control points. The proposed workflow emphasizes process standardization, inline quality control, and environmental optimization to achieve high first-pass yield and six sigma-level reliability. This research aims to guide engineers and manufacturers in evolving their SMT operations toward robust, scalable, and defect-resilient systems aligned with Industry 4.0 principles.
| 19 |
Author(s):
shruthi B N.
Page No : 1-4
|
Optimizing Industrial Automation: PLC-HMI Integration Strategies
Abstract
The integration of Programmable Logic Controllers (PLCs) with Human-Machine Interfaces (HMIs) plays a pivotal role in enhancing automation systems across industrial domains. This paper explores the seamless communication between PLCs and HMIs, focusing on architecture, protocols, and application design considerations. A detailed overview is provided on how real-time process monitoring and control are achieved through efficient data exchange mechanisms such as Modbus, OPC UA, and Ethernet/IP. The study also highlights best practices for HMI design that ensure intuitive operator interaction, improved system diagnostics, and operational safety. A practical implementation using [mention specific PLC and HMI brands/models, e.g., Siemens S7-1200 and WinCC] demonstrates the integration methodology and validates system responsiveness, reliability, and user experience. The paper contributes to the body of knowledge by offering a scalable framework for PLC-HMI integration applicable to various industrial automation scenarios, thus enabling smarter and more adaptable manufacturing environments
| 20 |
Author(s):
Mr.Siddiqui A.S.
Page No : 1-4
|
A Study on the Agriculture Sector and the Problems Associated with it which has an Impact on the Farmers
Abstract
Farmers are the main pillars of Indian economy and a source of food security for the whole nation. Farmers suicide has emerged as a serious problem today in India, each year thousands of farmers commit suicide due to lower income and heavy debt, they don’t have access to market, new technologies and irritation facilities, their land is being taken away by private sectors, Contract farming, small holding of lands, climate change, food shortage, water, issues of droughts and floods have all affected the live of the farmers in a miserable way ,the income from cultivate is so low that they are now shifting from farms to non-farms sector for earning, 76% of the farmers have left cultivation, marginalised and small holder farmers are the worst affected by it. The government has launched many schemes and brought in technology advancement still those facilities have not reduced the number of suicide cases, its growing at a rapid speed. Farmers today belongs to the most vulnerable section of the society. We need to all farmers access to the market, create better infrastructure and road connectivity followed by free health care and education provisions for the farmers and their families, special food package and medical insurance for farmers and their families.
| 21 |
Author(s):
V.Poongavi.
Page No : 1-4
|
An Analysis of Lattices And Their Various Types in Algebra
Abstract
This paper explores lattices in algebra, highlighting their structure and applications across
mathematics and computer science. Lattices, which originate from order theory, are partially
ordered sets where each pair of elements has a unique least upper bound and greatest lower
bound. Key types include distributive lattices, significant in Boolean algebra due to their
distributive properties, and modular lattices, which are useful in vector spaces, projective
geometry, and finite group classification. Additionally, complete, bounded, and complemented
lattices address specific mathematical challenges, making lattices a critical topic in modern research.
| 22 |
Author(s):
Aayush Gaurav.
Page No : 1-4
|
Comparative Analysis of Technical and Fundamental Analysis in Stock Market Investment: A Holistic Approach to Optimizing Investment Strategies
Abstract
Stock market investment is a multifaceted process requiring robust analytical frameworks to navigate its inherent complexities. Technical analysis, focusing on historical price patterns and market trends, and fundamental analysis, emphasizing a company’s intrinsic value, represent two cornerstone methodologies for investment decision-making. This research paper conducts a comprehensive comparison of these approaches, evaluating their theoretical foundations, practical applications, and effectiveness across varying market conditions. Drawing on quantitative data, qualitative insights, and real-world investor behaviour, the study highlights the strengths and limitations of each method. It further explores the efficacy of hybrid models that integrate both approaches to enhance risk-adjusted returns. Findings suggest that while technical analysis excels in short-term, volatile markets, fundamental analysis is superior for long-term value creation. Hybrid strategies, however, offer a balanced approach, optimizing timing and selection for diverse investor profiles. Recommendations are provided for individual investors, educators, and policymakers to foster informed and adaptive investment practices.
| 23 |
Author(s):
Gowda Varun Krishnamurti.
Page No : 1-4
|
A Comprehensive Survey on Programmable Logic Controllers (PLCs)
Abstract
Programmable Logic Controllers (PLCs) are widely used in modern industrial automation for managing real-time control systems across manufacturing, energy, and utility sectors. Originally developed to replace complex relay circuits, PLCs now serve as intelligent, programmable devices capable of executing sophisticated logic with high reliability. Their modular architecture supports diverse industrial tasks and seamless integration with Supervisory Control and Data Acquisition (SCADA) systems and Industrial Internet of Things (IIoT) platforms. This paper surveys the architecture, application, and educational relevance of PLCs. Key contributions include enhanced operational efficiency, improved fault detection, real-time monitoring, and increased automation. Despite widespread industry adoption, the integration of PLC education into engineering curricula remains limited. This paper emphasizes the need to address this gap to prepare students for evolving industry demands. Future trends such as edge computing, AI integration, and cyber-physical systems are also discussed, highlighting the ongoing evolution of PLCs within the Industry 4.0 framework
| 24 |
Author(s):
Lokesh Singh.
Page No : 1-4
|
A Study on Customer Satisfaction Levels in Quick Commerce Platforms in India
Abstract
Quick commerce, or Q-commerce, is changing the way people shop by offering
super-fast delivery of groceries and daily essentials—often in just 10 to 30 minutes.
This model is gaining huge popularity in India, especially in busy cities where people
value speed and convenience. Platforms like Blinkit, Zepto, Swiggy Instamart, and
BBNow are leading this trend by helping customers get what they need without
stepping out of their homes.
This study looks at what really matters to customers when they use these Q
commerce services. What makes them happy? What keeps them coming back? To
find out, a survey was conducted with 300 people who regularly use these platforms.
The survey focused on five key areas:
• How fast the delivery is
• Whether the items they want are available
• How easy the app is to use
• Whether prices are reasonable
• How good the customer service is
After analyzing the responses, two things stood out: delivery speed and app usability
are the most important factors for customer satisfaction. People really appreciate it
when their orders arrive quickly, especially when they’re in a rush or need something
urgently. They also like using apps that are simple, smooth, and don’t crash or
confuse them.
Other factors like having a wide variety of products, fair pricing, and helpful
customer service do matter—but not as much as speed and a user-friendly app. In
fact, since most Q-commerce orders are small and routine (like milk, snacks, or
vegetables), people are less focused on deep discounts or talking to customer
support—what they really want is quick, hassle-free service.
The findings of this study can help Q-commerce companies improve their services.
If they focus on making deliveries even faster and keeping their apps easy to use,
they’ll likely keep more customers happy and loyal. The study also suggests that
future research could look into things like how delivery services can be made more
eco-friendly, or how customer needs vary in smaller towns and cities.
In short, Q-commerce is not just about fast delivery—it’s about making life easier.
And when done right, it has the power to change how India shops, one quick delivery
at a time.
lo
| 25 |
Author(s):
GAZALA USMANI, MANINATH NISHAD, ANKIT PANDEY.
Page No : 1-4
|
An IoT Instrumented Smart Agricultural Monitoring and Irrigation System
Abstract
These days, in the agriculture sector farmers are facing major problems regarding irrigation. Due to over- irrigation and under-irrigation, the crops can be damaged. This work development of an IoT instrumented smart agricultural monitoring and irrigation system. In this paper, an IoT platform based on ThingSpeak and NodeMCU is demonstrated, which will help the farmer to control the irrigation by using a PC or smartphone from anywhere and anytime, to monitoring the moisture and temperature parameter and reduce his efforts and also to optimize the use of water. Sensors value is sent to the IoT platform and if a value is below the threshold a notification will be sent to the user through E-mail to take suitable action.
| 26 |
Author(s):
Bharath Kumar.
Page No : 1-4
|
AI-Based Predictive Models for Engineering Nanostructures for Bioremediation
Abstract
Bioremediation, utilizing microorganisms or plants to degrade pollutants, faces challenges in dealing with difficult contaminants like heavy metals and organic compounds. Nanotechnology has emerged as a promising tool to enhance bioremediation, owing to the unique properties of nanomaterials such as high surface area and chemical reactivity. However, the design of effective nanomaterials for environmental cleanup remains complex due to the variability in material properties and pollutant interactions. Traditional trial-and-error methods for nanomaterial design are resource-intensive and time-consuming. Artificial intelligence (AI) has become a transformative solution to optimize nanomaterial design and performance. AI-powered predictive models, leveraging large datasets and advanced algorithms, can simulate nanomaterial behavior, enabling the identification of optimal properties for pollutant removal. Machine learning (ML) techniques, such as supervised learning, unsupervised learning, and reinforcement learning, play critical roles in predicting nanomaterial performance and optimizing synthesis parameters. Additionally, AI enables the use of multiscale modeling to predict nanomaterial behavior across atomic, molecular, and larger scales, improving their interaction with pollutants and microbial communities. By integrating AI with high-throughput screening systems, researchers can rapidly evaluate and optimize nanomaterials for effective bioremediation, accelerating the development of sustainable environmental solutions.
| 27 |
Author(s):
Shaistha H.
Page No : 1-4
|
AI-Driven Synthesis of Antimicrobial Nanomaterials for Infection Control
Abstract
Antimicrobial resistance (AMR) is a major global health threat, as it undermines the effectiveness of traditional antibiotics against multidrug-resistant (MDR) pathogens. To address this issue, the use of nanomaterials, particularly nanoparticles, has gained significant attention due to their unique antimicrobial properties. Nanoparticles exhibit potent antimicrobial effects by disrupting bacterial cell membranes, generating reactive oxygen species, and interfering with bacterial metabolism. However, the synthesis of antimicrobial nanoparticles requires precise control over their properties such as size, shape, surface charge, and composition. Traditional approaches to nanoparticle synthesis are often resource-intensive and time-consuming. To streamline this process, artificial intelligence (AI) has emerged as a powerful tool for designing, optimizing, and automating the synthesis of antimicrobial nanomaterials. AI-driven models, including machine learning (ML), can predict nanoparticle properties and optimize synthesis conditions, reducing the time and cost required for nanoparticle development. Furthermore, AI can integrate with high-throughput synthesis techniques to rapidly generate and test large numbers of nanoparticle formulations. Real-time monitoring and control of the synthesis process, enabled by AI, allows for dynamic adjustments to maintain optimal conditions, ensuring reproducibility and scalability. While challenges such as the need for large, high-quality datasets and model generalization across nanoparticle systems persist, AI holds immense potential to revolutionize the design and production of antimicrobial nanoparticles, offering novel solutions to combat AMR in the future.
| 28 |
Author(s):
Akshaya R.
Page No : 1-4
|
A Study on impact of Hr practices on employee’s innovation and creativity with reference to Adapton global service
Abstract
This study investigates how Human Resource (HR) practices influence innovation and creativity among employees at Adapton Global Services. In an era of competitive market dynamics, fostering innovation is a critical driver of sustained growth. HR practices, including recruitment, training, rewards, and performance management, are key levers for nurturing creative behaviors. Using a structured questionnaire distributed to 170 employees, the study analyzes the impact of these HR interventions using descriptive statistics, correlation, and chi-square tests. The findings emphasize the importance of supportive HR frameworks in enhancing creative thinking, motivation, and collaborative culture in the workplace
| 29 |
Author(s):
Hemangi Vasudev Patil.
Page No : 1-4
|
A Study of Future Remote Work and Its Strategic Role in Business Evolution
Abstract
Remote work increasingly integrated into business practices has evolved into a strategic component of business evolution impacting various aspects from employee experience to operational efficiency companies are leveraging remote work for enhanced flexibility global talent access and reduced overhead costs however challenges related to communication team cohesion and cyber security remains strategic remote work planning involves adapting policies investing in technology and fostering a culture of trust and open communication.
| 30 |
Author(s):
Prathmesh Patil.
Page No : 1-5
|
Health Monitoring of Soldiers Using GSM
Abstract
In high-risk environments such as battlefields, monitoring a soldier’s health in real-time can be vital for saving lives and delivering prompt medical care. This work introduces a compact health monitoring solution equipped with GSM technology for use by military personnel using a PIC18F4550 microcontroller interfaced with biomedical sensors such as the MAX30102 (for pulse and SpO2), AD8232 (ECG), and DS18B20 (temperature). It transmits key health indicators and location details to a remote monitoring center via a SIM900A GSM module. A 16x2 LCD display using the I2C protocol shows real-time health data to the soldier directly. This budget-friendly setup improves both the safety and remote health tracking capabilities for soldiers.
| 31 |
Author(s):
Yash Dudhe.
Page No : 1-5
|
Transforming website Navigation and Interpretation with a Retrieval Augmented Generation chatbot
Abstract
With the exponential growth of digital content,
website navigation and information retrieval have become
increasingly complex for users. Traditional search mechanisms
often fail to provide precise and context-aware results, leading to
inefficiencies in browsing. This paper presents a novel approach to
website navigation and interpretation using a Retrieval-Augmented
Generation (RAG) chatbot integrated with a Large Language Model
(LLM). The chatbot leverages retrieval-based techniques to extract
relevant website content while utilizing generative AI to enhance
user interaction and query resolution. Implemented using Streamlit,
the proposed system efficiently decodes website structures and
provides intuitive responses, reducing user effort in information
discovery. Our evaluation demonstrates that the chatbot
significantly improves navigation efficiency and accuracy compared
to conventional website search functionalities. This research
contributes to the advancement of AI-driven website accessibility
and presents opportunities for further enhancements in web-based
information retrieval.
| 32 |
Author(s):
Swati Bhati.
Page No : 1-5
|
MEDIATION
Abstract
MEDIATION
| 33 |
Author(s):
Rakesh Gowda.
Page No : 1-5
|
Algorithmic Sustainability: Designing Green AI Models for Energy-Efficient Computing
Abstract
The growing demand for artificial intelligence (AI) systems has led to an increase in energy consumption, raising concerns about the environmental impact of AI technologies. Algorithmic sustainability is emerging as a crucial concept in addressing these concerns, focusing on designing AI models and systems that are energy-efficient, environmentally friendly, and socially responsible. This paper explores the principles of green AI and algorithmic sustainability, highlighting the importance of developing AI systems that optimize energy consumption without compromising performance. It discusses the environmental challenges posed by AI's energy demands, explores innovative solutions for reducing the carbon footprint of AI systems, and examines the future potential of sustainable AI models. Through the analysis of case studies and emerging practices, this paper emphasizes the need for integrating sustainability into AI research and development to create a more sustainable technological future.
| 34 |
Author(s):
Suresh P.
Page No : 1-5
|
Hybrid Intelligence: The Future of Human-AI Collaborative Creativity in Science and Art
Abstract
Hybrid intelligence, the collaboration between human cognition and artificial intelligence (AI), represents a promising frontier in both scientific and artistic fields. This paper explores the concept of hybrid intelligence, where humans and AI systems work together to enhance creativity, problem-solving, and innovation. The integration of AI tools in scientific research and artistic expression offers new opportunities for pushing the boundaries of human potential. This paper delves into how hybrid intelligence is transforming creativity in science and art, focusing on the symbiotic relationship between human intuition and AI's computational power. It discusses the potential benefits and challenges of human-AI collaboration, and presents case studies where hybrid intelligence has led to groundbreaking discoveries and artistic achievements. The paper also examines the future implications of hybrid intelligence for enhancing human creativity and the role of AI as a co-creator in various domains.
| 35 |
Author(s):
Vedamurthy.
Page No : 1-5
|
AI-Powered Citizen Science: Crowd-Learning, Data Verification, and Public Engagement
Abstract
Citizen science, a collaborative effort where non-experts contribute to scientific research, has seen exponential growth with the integration of artificial intelligence (AI). This paper explores the role of AI in enhancing citizen science by facilitating crowd-learning, improving data verification processes, and fostering greater public engagement. Through the application of machine learning algorithms and data analytics, AI can streamline the collection and analysis of large datasets, improving the accuracy and efficiency of citizen-led research. Furthermore, AI-powered platforms can empower individuals from diverse backgrounds to actively participate in scientific discovery, leading to more inclusive and democratized research. This paper examines various case studies where AI has been successfully implemented in citizen science projects, offering insights into how these technologies are reshaping the landscape of scientific inquiry and public involvement.
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Author(s):
Aishwarya. S.
Page No : 1-5
|
Multimodal AI for Disability Inclusion: Breaking Barriers in Assistive Technologies
Abstract
Artificial Intelligence (AI) has the potential to transform the way society supports individuals with disabilities. By integrating multimodal AI systems into assistive technologies, it is possible to create more inclusive, adaptive, and personalized solutions that empower individuals to navigate the world with greater ease. This paper explores the role of multimodal AI in disability inclusion, with a focus on its application in assistive devices and systems. It examines the integration of various AI modalities, such as computer vision, natural language processing, and speech recognition, to design technologies that address a wide range of accessibility challenges. The paper also highlights current developments, the impact of multimodal AI on independence and quality of life for individuals with disabilities, and the ethical considerations that arise in the development of such technologies.
| 37 |
Author(s):
YUVAN KUMAR SALINA.
Page No : 1-5
|
Privacy preservation techniques in machine learning
Abstract
The exponential expansion of machine learning (ML) applications in a variety of fields has raised concerns about the privacy of user data. Strong privacy-preserving methods must be developed because sensitive data used in model training may unintentionally be revealed. Under the headings of data anonymization, differential privacy, federated learning, homomorphic encryption, and secure multi-party computation, this survey offers a thorough summary of the privacy-preserving techniques currently used in machine learning. We examine their methods, advantages, drawbacks, and potential uses. In order to guarantee privacy compliance in ML-driven systems, the paper also lists the main obstacles, unresolved research issues, and necessary future paths.
| 38 |
Author(s):
SIDDHRTH SHARMA.
Page No : 1-5
|
Real-Time Face Recognition Automatic Student Attendance Management
Abstract
In educational institutions,maintaining accurate and efficient student attendance records is essential but often time-
consuming when done manually. This project
presents a Real-Time Face Recognition-
Based Automatic Attendance Management
System designed to automate the process of
recording student attendance using facial
recognition technology. By integrating
computer vision and machine learning techniques, specifically through the use of
OpenCV and deep learning-based face
recognition algorithms, the system captures
and identifies student faces in realtime via a
webcam or surveillance camera.
| 39 |
Author(s):
Shubham Sharma .
Page No : 1-5
|
A Practical Approach to Making Recommendation Systems Fair and Understandable with Graph Neural Networks
Abstract
Recommendation systems are being used a lot in helping users find content they may like, especially on shopping and OTT services. But the problem is, many of these systems are working in certain ways that people cannot see or understand. They often
don’t explain how they choose what to show, and sometimes, they are not fair to all users.
In this paper, we present a recommendation system built using Graph Neural Networks (GNNs),
specifically a Graph Attention Network (GAT). This model helps highlight which past interactions matter
the most, making it easier to explain why something is being recommended. At the same time, we apply techniques to reduce bias like making sure that less popular items still have a chance to get recommended.We have tested our model using the data from Amazon Reviews. The results showed our
model performs as well as other popular methods/
models while doing a better job of balancing
recommendations and providing explanations that are easier to understand. We also talk about the challenges and future directions for building recommendation systems that are smarter, fairer, and more transparent.
| 40 |
Author(s):
Mohammed Azam.
Page No : 1-5
|
Transformer Models for Predicting Bacteriophage-Host Relationships
Abstract
Bacteriophages, or phages, are viruses that specifically infect bacteria, and they have garnered attention as potential alternatives to antibiotics in the face of rising antimicrobial resistance (AMR). Understanding the complex interactions between bacteriophages and their bacterial hosts is fundamental to developing effective phage therapies. Traditional methods of studying phage-host relationships rely on empirical and experimental approaches, which are often time-consuming and labor-intensive. In contrast, machine learning models, particularly transformer-based deep learning models, have shown considerable promise in predicting these interactions by leveraging large datasets of genomic sequences. This paper explores the application of transformer models for predicting bacteriophage-host interactions, highlighting their potential benefits, challenges, and future directions in phage therapy and microbiome research.
| 41 |
Author(s):
Akshat Kumar .
Page No : 1-5
|
AI – Based Multiple Disease Prediction System
Abstract
The advancement of Artificial
Intelligence (AI) in the healthcare domain
has paved the way for intelligent diagnostic
tools capable of predicting diseases with
remarkable
accuracy. This research
introduces a unified Multiple Disease
Prediction System designed to forecast the
likelihood of three significant illnesses—
Diabetes, Heart Disease, and Parkinson’s
Disease—by analyzing patient-specific
health parameters. Developed using Python
and deployed through the Streamlit
framework, the system utilizes machine
learning models trained on relevant medical
datasets. A notable feature of this system is
the integration of an AI-driven symptom
checker powered by Google Gemini API,
which interprets user-described symptoms
in natural language to provide potential
diagnoses. The application aims to enhance
accessibility to preliminary health screening
and support medical professionals by
offering rapid, data-driven insights.
Experimental evaluations reveal high
prediction precision, affirming the system’s
practical effectiveness and potential
contribution to intelligent healthcare.
| 42 |
Author(s):
Rahul Bhosale .
Page No : 1-5
|
Experimental Analysis on Design and Development of Air Cooler with Integrated Air Conditioning
Abstract
Because of today’s Transforming technology, updating traditional products/electronics with smart features is essential to improve both the way things operate and how users are comfortable. Conventional air coolers become smart by linking normal air conditioning components to them. A compressor, evaporator and a condenser improves and increases the function of an air cooler. An air cooler works by turning water into gas that helps create cold air. While the open air method of an air cooler may not help in wet weather, air conditioners can effectively cool down your space in any weather. If you include items such as a compressor and condenser along with the evaporator, the design of an air cooler becomes more like an air conditioning unit. As part of making the system smarter, a new automated temperature control feature is added to the energy optimization options.
| 43 |
Author(s):
Dr. S. Usha, Ranjithamani K.
Page No : 1-5
|
ENHANCING PRODUCTION PLANNING DECISIONS THROUGH MATHEMATICAL OPTIMIZATION WITH EXCEL SOLVER
Abstract
This paper explores the application of mathematical optimization techniques to enhance production planning decisions using Excel Solver. The objective is to demonstrate how organizations can improve efficiency, reduce costs, and optimize resource utilization by formulating and solving linear programming models within a spreadsheet environment. The study involves the development of a production planning model that integrates constraints such as labor hours, material availability, demand requirements, and production capacities. Excel Solver is employed as a user-friendly and accessible tool for implementing these optimization models, enabling decision-makers without advanced programming skills to perform complex analyses. Results show that the optimized plans significantly outperform heuristic or manual approaches, yielding higher profitability and better resource alignment. The findings highlight the practicality and effectiveness of Excel Solver in operational decision-making contexts, particularly for small to medium-sized enterprises seeking low-cost optimization solutions. This research underscores the importance of incorporating quantitative methods into business processes and illustrates how spreadsheet-based tools can support data-driven, strategic production planning.
| 44 |
Author(s):
MEGADHARSHINI.B.
Page No : 1-5
|
A STUDY ON EMPLOYEE INDUCTION AND ORIENTATION WITH REFERENCE TO MAHLE ENGINE COMPONENTS INDIA PVT LTD
Abstract
This study evaluates the effectiveness of induction and orientation programs at Mahle Engine Components India Pvt Ltd. and their impact on employee adjustment and performance. Using a descriptive research design, primary data were collected from 215 employees through structured questionnaires and analyzed using SPSS software. Results show that while the induction program is largely perceived as useful, employees expressed a need for more interactive and department-specific sessions. Those who underwent structured orientation demonstrated better role clarity and quicker adaptation to the workplace. The study recommends improvements such as regular feedback mechanisms, departmental mentor involvement, and digital onboarding tools to enhance employee engagement and organizational integration.
| 45 |
Author(s):
ANUSHIA.A.
Page No : 1-5
|
A STUDY ON EMPLOYEE COMPENSATION AND BENEFIT WITH REFERENCE TO HOLLOWBRANE MEMBRANE TECHNOLOGIES
Abstract
This study explores the compensation and benefits framework at Hollowbrane Membrane Technologies Pvt. Ltd., a company in the sewage water filtration sector. It examines both direct (salary, bonuses) and indirect (insurance, leave, retirement benefits) forms of compensation. Using surveys and statistical tools like chi-square, correlation, and regression, the study assesses employee perceptions of fairness, satisfaction, and alignment with responsibilities. Results show that transparent, performance-linked, and legally compliant compensation systems positively impact morale, retention, and organizational effectiveness. The findings offer actionable insights for companies aiming to align compensation strategies with employee needs and business goals.
| 46 |
Author(s):
PREETHA.J.
Page No : 1-5
|
A STUDY ON AWARENESS AND EFFECTIVE UTILISATION OF ESI BENEFITS AMONG EMPLOYEES WITH REFERENCE TO WONJIN AUTOPARTS INDIA PVT LTD
Abstract
This study investigates the awareness and effective utilization of the Employees' State Insurance (ESI) scheme among employees at WONJIN Auto Parts India Private Limited. The ESI scheme, a pivotal social security initiative in India, offers various benefits including medical, maternity, sickness, disablement, dependent, and funeral services. Employing a descriptive research design, data were collected from 200 employees selected through simple random sampling. Statistical tools such as ANOVA, chi-square test, regression, and correlation analyses were utilized to assess the level of awareness and factors influencing the effective utilization of ESI benefits. The findings provide insights into employees' understanding and usage of ESI services, leading to recommendations aimed at enhancing the scheme's effectiveness within the organization.
| 47 |
Author(s):
Ashwini Gurung, Dr. Deepa Chauhan.
Page No : 1-6
|
ROLE OF MEDIA IN SHAPING PUBLIC OPINION
Abstract
In the fast-paced information age of today, media has a strong influence on how the public perceives and responds to the world around them. This study delves into how various types of media—ranging from traditional news sources to contemporary social media sites—not only educate but actually shape public opinion. It looks at how media decides what issues people care about, how they make sense of events, and even if they feel comfortable sharing their opinions with others.
The research shows that the media has an effect on public opinion through a number of mechanisms, including framing particular issues over others (agenda-setting), emotionally manipulating audiences via word selection and imagery (framing), and affirming beliefs through continual exposure. Social media, specifically, is discovered to amplify opinion polarization through algorithmic echo chambers. Although its scope is wide, media influence also has boundaries, particularly because of differences in culture, the fast-changing digital landscape, and the challenges of distinguishing between media effects and other socializing factors.
The research indicates the immediate necessity for improved media literacy, ethical journalism standards, and more responsibility for online platforms. The future of research must address the impact of media algorithms, international comparisons, and the long-term effect of digital content—especially on young audiences. In a world where media influences not only information, but perception itself, knowing its role in shaping public opinion is more crucial than ever.
| 48 |
Author(s):
S. Anusha Rani.
Page No : 1-6
|
HEART DISEASE PREDICTION SYSTEM USING MACHINE LEARNING
Abstract
Cardiovascular disease is one of the most prevalent causes of death worldwide, and early detection is crucial to prevent additional deaths and to increase survival rates. Conventional diagnosis by examining electrocardiograms( ECG), blood and clinical approach is time-consuming and expensive methods, which are prone to human error. A Heart Disease Prediction System leveraging various Machine Learning algorithms including Logistic Regression and Support Vector Machine predicts patient risk pretty accurately.
| 49 |
Author(s):
Vaibhav Kathuria.
Page No : 1-6
|
Environment and sustainability policy effectiveness: Synthesising and Analysing Indexes with Indicators & Impact
Abstract
To understand effectiveness of policies focussed on the environment, understanding certain global indexes can be essential. While there are a number of indicators, metrics and indexes, this paper would focus on a few important ones via some key indexes. In this research the focus would be on the following indexes: the Environmental Performance Index, the Green Growth Index and the OECD Environmental Policy Stringency index. Understanding these indexes with indicators and synthesising important aspects can be of importance to understand policies impact and the actual additions in value to the environment for sustainability. The scope of an index and its importance can be both global as well as local. The important aspects of the aforementioned indexes would be highlighted in this research in a cohesive manner of analysis and a discussion-like format. The paper helps in the derivation of some robust insights which could potentially be integrated in frameworks for environment policy effectiveness at different stages of a policy planning and implementation process. The challenges, changes and some key aspects of the mentioned indexes are discussed. Highlighting challenges also opens the possibility of deriving solutions and feedback.
| 50 |
Author(s):
Aarchi Goyal.
Page No : 1-6
|
A Study on Latest Recruitment Trends
Abstract
This research explores the evolving landscape of recruitment trends, focusing on the influence of digital technologies, diversity and inclusion initiatives, and organizational culture on modern hiring practices. With the increasing reliance on artificial intelligence, social media, and digital platforms, recruitment has undergone a fundamental transformation. The study also examines variations across industry sectors and assesses the effectiveness of diversity, equity, and inclusion (DEI) programs. A quantitative methodology was employed using survey data from HR professionals and recruiters across multiple sectors. The findings suggest that organizations adopting innovative digital tools and inclusive hiring practices report improved applicant quality, higher candidate acceptance rates, and better employee retention. The study offers actionable insights for organizations aiming to remain competitive in attracting top talent amid shifting workforce expectations.
| 51 |
Author(s):
zunaira jasmine.
Page No : 1-6
|
A Laboratory-Based Assessment of Pervious Bituminous Pavement for Urban Drainage
Abstract
Urban flooding in under-bridge areas poses significant challenges, leading to traffic congestion, road deterioration, and increased maintenance costs. Traditional drainage systems often fail to efficiently manage excess storm water, exacerbating these issues. This study investigates the use of pervious bituminous pavement as an innovative and sustainable drainage solution. By integrating engineered void structures, this pavement allows water infiltration, reducing surface runoff and enhancing groundwater recharge. The research focuses on evaluating its permeability, durability, and overall performance under varying environmental and traffic conditions. Laboratory tests, including softening point, penetration, ductility, soil compaction, and California Bearing Ratio (CBR), were conducted to determine the suitability of the materials. The results demonstrate that pervious bituminous pavement improves drainage efficiency, minimizes hydroplaning risks, and enhances road resilience, making it a viable alternative for under-bridge storm-water management.
| 52 |
Author(s):
Rajat.
Page No : 1-6
|
Real-Time Object Detection to Assist the Visually Impaired
Abstract
Real-time object detection is a much-needed subsection of computer vision and can be applied to autonomous vehicles, surveillance, medical imaging, and robotics. This research paper provides an overview of real-time object detection strategies, specifically within the architectures of real-time object detection methods such as SSD (Single Shot Detector), and with Faster R-CNN based on a deep learning architecture. This paper also discusses the advantages of these architectures, limitations, and performance metrics. The proposed approach discussed in this paper integrates a hybrid deep learning method optimized for low-latency accuracy in real-time detection. The Convolutional Neural Network (CNN) is essential to modern object detection networks, and is the backend of OpenCV, which is an open-source based computer vision library supporting computer-based vision applications. OpenCV library contains over 2,500 optimized algorithms to implement for tasks such as face recognition, object tracking. Its open-source nature makes it highly inexpensive and adaptable to a business or research setting, greatly enhancing the innovation of real-time computer vision applications.
| 53 |
Author(s):
Bhagat Devika Babasaheb .
Page No : 1-6
|
Formulation and evaluation of anti inflammatory gel of diclofenac sodium
Abstract
The diclofenac sodium gels were prepared by using different concentration of carbopol for topical drug delivery. Carbopol High Molecular weight water soluble homo polymer, it possess very high viscosity in low concentration, transparency, film forming properties and are useful in formation of gel. The gel was prepared and evaluated for pH, Spread ability, Homogeneity, Drug Content. The percentage drug release was 99%.
| 54 |
Author(s):
Sandhya. D.
Page No : 1-6
|
A Study on HR Analytics in Decision making process with reference to Diamond Engineering Chennai Pvt Ltd
Abstract
Human Resource (HR) analytics has emerged as a critical tool in enhancing decision-making processes within organizations. This study explores the role of HR analytics in decision-making with reference to Diamond Engineering Chennai Pvt. Ltd. By leveraging data-driven insights, HR analytics enables organizations to optimize workforce planning, talent acquisition, performance management, and employee engagement.
At Diamond Engineering Chennai Pvt. Ltd., HR analytics plays a pivotal role in identifying key workforce trends, predicting attrition rates, and improving overall employee productivity. Through the use of advanced analytics tools, the company can assess employee performance metrics, streamline recruitment strategies, and enhance training and development programs.
| 55 |
Author(s):
Balaji B.
Page No : 1-6
|
A study on Employee morale with reference to micro concept tools pvt ltd
Abstract
Employee morale is a critical factor influencing productivity, engagement, and overall
organizational success. This study aims to evaluate the levels of morale among
employees at Micro Concept Tools Pvt. Ltd., identifying key influencing factors. Using
descriptive research design and statistical tools like chi-square and ANOVA, the study
finds that while most employees are satisfied with compensation and environment,
issues like communication and career growth require attention. The paper
recommends structured engagement and recognition programs to enhance morale.
| 56 |
Author(s):
ARUN V.
Page No : 1-6
|
A STUDY ON EMPLOYEE ABSENTEEISM WITH REFERENCE TO MULTIVISTA GLOBAL PRIVATE LIMITED
Abstract
The “ A Study on Employee Absenteeism” project , carried out by Multivista Global Private Limited, The goals of this study are to analyse overall attendance data and determine absenteeism rates, to increase employee productivity by cutting down on absences, to identify the major causes of absences in a given department, to suggest management strategies to cut down on absences, to identify the causes of both avoidable and unavoidable absences, and to learn about the different facilities and employee welfare programmes available.
| 57 |
Author(s):
Lovkush.
Page No : 1-7
|
Role of subsistence entrepreneurship in employment generation
Abstract
Subsistent entrepreneurship, often characterized by small-scale, self-employed ventures primarily aimed at meeting the basic needs of entrepreneurs and their families, plays a vital yet underappreciated role in employment generation. This report explores how such grassroots-level entrepreneurial activities contribute to alleviating unemployment, especially in developing and rural economies. By creating informal job opportunities, promoting self-reliance, and fostering local economic development, subsistent entrepreneurs act as a buffer against economic shocks and limited formal employment. The report analyzes case studies, economic data, and policy implications to highlight the potential of supporting subsistent entrepreneurship as a sustainable strategy for inclusive employment generation. Challenges such as lack of access to capital, training, and markets are also discussed, along with recommendations to enhance the impact of this entrepreneurial sector.
| 58 |
Author(s):
S.AARTHI.
Page No : 1-7
|
A STUDY ON DERIVATIVES ANDITSAPPLICATION
Abstract
This study explores the concept of derivatives and their diverseapplications in various fields. Derivatives, which measure the rate of changeofa function, are a fundamental tool in calculus. The study examinesthemathematical foundations of derivatives and their applications in optimizationproblems, physics, engineering, economics, and computer science. Theresearch highlights the significance of derivatives in modelling real-worldphenomena, predicting behaviour, and making informed decisions. It alsodiscusses the limitations and challenges associated with derivative-basedmodels. The study aims to provide a comprehensive understandingofderivatives and their applications, making it a valuable resource for students, researchers, and professionals across various disciplines.
| 59 |
Author(s):
Dr.Ranjith Somasundaran Chakkambath; Gouri Krishna; Sneha Verma;.
Page No : 1-7
|
The Ethical Use of AI in Personalized Learning – A Student Perspective
Abstract
Artificial Intelligence (AI) is transforming education through personalized learning, offering adaptive content and automated assessments. However, its ethical implications raise concerns about data privacy, algorithmic bias, transparency, and equitable access to education. This study examines students' perspectives on the ethical use of AI in personalized learning, focusing on awareness, concerns, and perceived benefits. Using a descriptive research design and convenience sampling, the study targets students from the Ernakulam district who have engaged with AI-driven educational tools. The research explores issues such as AI’s impact on student autonomy, fairness in learning recommendations, and the potential over-reliance on technology. Findings aim to highlight the balance between AI’s benefits and ethical risks, emphasizing the need for transparent, inclusive, and secure AI-driven education systems. The study contributes to ongoing discussions on how AI can enhance learning while safeguarding student rights in the evolving educational landscape.
| 60 |
Author(s):
Muskan Chauhan .
Page No : 1-7
|
Corporate Social Responsibility-A Review of impact and practices in TCS
Abstract
Corporate Social Responsibility (CSR) is one of the important factors that contributes to the public image, internal culture, and above all, the success of technology firms in today competitive business world. The present paper discusses the role and implementation of CSR practices in the technology sector, which is focused on Tata Consultancy Services (TCS).It looks at how CSR helps with getting and keeping workers which is very important for the long-term success and expansion of tech firms. Based on books and articles published from 2008 to 2024 used in this paper it shows the good things and bad problems of adding CSR into business plans. CSR activities are shown to greatly improve employee satisfaction, boost a feeling of organizational commitment, and build the company’s brand reputation. These results then help long-term business sustainability and stakeholder trust. At TCS, CSR initiatives reflect its commitment to the community and sustainable development along with ethical practices. The firm’s strategic alignment of social responsibility with business objectives has created a positive working environment, fostered trust among employees, and built a competitive edge in the fast-evolving tech industry. Greater emphasis is also laid on the challenges in implementing CSR, like dealing with complex regulatory requirements, making adequate resources available, and handling the trade-off between profits and social obligations. In spite of these challenges, CSR continues to be an extremely instrumental process through TCS and other technology companies in maintaining ethical beliefs, providing services to society, and achieving long-term success within a changing and innovative industry.
| 61 |
Author(s):
Sanala Vaishnavi.
Page No : 1-7
|
Decentralized Voting System Using Blockchain
Abstract
—Decentralized voting using Ethereum blockchain is a secure, transparent and tamper-proof way of conducting online
voting. It is a decentralized application built on the Ethereum blockchain network, which allows participants to cast their votes and view the voting results without the need for intermediaries.
In this system, votes are recorded on the blockchain, making it impossible for anyone to manipulate or alter the results. The use
of smart contracts ensures that the voting process is automated, transparent, and secure. The use of the blockchain technology
and the implementation of a decentralized system provide a reliable and cost-effective solution for conducting trustworthy and fair elections.
| 62 |
Author(s):
Kona Siva Chakradhar Karthik.
Page No : 1-7
|
BLOCKCHAIN-BASED FUND ALLOCATION AND TRACKING MECHANISM FOR STATE GOVERNMENT
Abstract
The state government's work involves numerous transactions across various operations such as initiatives, projects, contracts, and farmer schemes. A major challenge faced by top governments is low-level corruption, which is difficult to trace and hinders state progress. This corruption slows down development and affects the delivery of essential services to the needy.
To address this, a secure system like Blockchain is essential. Blockchain tracks all transactions securely and transparently using cryptography and timestamps. It ensures that each transaction is tamper-proof and verifiable, improving efficiency and trust in government operations. This system is particularly effective in managing funding programs and schemes by providing clear, secure records.
| 63 |
Author(s):
Pillala Dhanarjuna.
Page No : 1-7
|
AUTOMATED ROAD DAMAGE DETECTION USING UAV IMAGES AND DEEP LEARNING TECHNIQUES
Abstract
Auto-detection of road damage is achieved through deep learning using images absorbed by unmanned aircraft. Maintaining street infrastructure is of great importance for safe and sustainable transportation, but manual data collection is often labor-intensive and dangerous. To address this, we propose leveraging UAVs and AI to significantly improve detection efficiency and accuracy. Object detection and localization in UAV imagery utilizes yolov4, yolov5, and yolov7 algorithms, which have been trained on the rdd2022 dataset from China and a dataset of Spanish roads. YOLOv5 yielded 59.9% mAP@.5 whereas YOLOv5 equipped with a Transformer Prediction Head attained surprisingly high 65.70% mAP@.5 and YOLOv7 outperformed both achieving 73.20% mAP@.5. UAV-based deep learning systems show considerable promise for automated detection of road damage offering a robust foundation for future smart infrastructure research endeavors.
| 64 |
Author(s):
Dr. Mano Ranjitham E.
Page No : 1-7
|
A Review on Artificial Intelligence in Education: Insights and Future Perspectives for Students, Teachers, and Classrooms
Abstract
AI is revolutionizing traditional teaching and learning methods in education, creating new opportunities to enhance student engagement and optimize institutional processes. This review paper delves into the transformative role of Artificial Intelligence (AI) in education, emphasizing its potential to revolutionize learning and teaching in the 21st century. As AI technologies continue to advance, they are reshaping traditional educational practices, enhancing student engagement, and optimizing institutional operations. The integration of AI into educational systems has resulted in a paradigm shift in how students learn, teachers instruct, and schools function, paving the way for innovative solutions that were once thought to be unattainable.
The paper discusses the myriad benefits of AI in education, including improved accessibility for diverse learners, the reduction of educational inequalities, and the provision of data-driven insights that facilitate a holistic understanding of learners’ needs. By harnessing AI, educators can tailor instructional approaches to meet individual student requirements, fostering a more personalized learning experience. Additionally, the review examines the evolving roles of teachers and students in an AI-enhanced learning environment, highlighting the importance of collaborative approaches that blend human expertise with AI capabilities.
Despite its numerous advantages, the paper acknowledges the challenges and ethical considerations associated with AI integration, including concerns related to data privacy, algorithmic bias, and the potential loss of human interaction in learning contexts. Furthermore, it underscores the importance of policy collaboration in advancing AI in education, ensuring responsible and equitable implementation that addresses these challenges. By providing a comprehensive literature review, this paper aims to illuminate the current landscape of AI in education and its potential to transform educational outcomes for all stakeholders involved, ultimately contributing to the advancement of a more inclusive and effective educational system.
Keywords: Artificial Intelligence (AI), Education Technology, Learning Transformation, 21st Century Learning, AI Integration in learning
| 65 |
Author(s):
SAKSHI A. UNDE, DNYANESHWAR S. VYAVHARE ,DR. MEGHA T. SALVE.
Page No : 1-7
|
RECENT DEVELOPMENT IN THE USE OF INTRALESIONAL INJECTIONS KELOID TREATMENT
Abstract
Keloids are pathological scars presenting as nodular lesions that extend beyond the area of injury. They do not spontaneously regress, often continuing to grow over time. The abnormal wound-healing process underlying keloid formation results from the lack of control mechanisms self-regulating cell proliferation and tissue repair. Keloids may lead to cosmetic disfigurement and functional impairment and affect the quality of life. Although several treatments were reported in the literature, no universally effective therapy was found to date. The most common approach is intralesional corticosteroid injection alone or in combination with other treatment modalities. Triamcinolone acetonide (TAC) is the most commonly used intralesional corticosteroid. The aim of this article was to review the use of TAC, alone or in combination, in the treatment of keloid scars. The response to corticosteroid injection alone is variable with 50–100% regression and a recurrence rate of 33% and 50% after 1 and 5 years, respectively. Compared to verapamil, TAC showed a faster and more effective response even though with a higher complication rate. TAC combined with verapamil was proved to be effective with statistically significant overall improvements of scars over time and long-term stable results. TAC and 5-fluorouracil (5-FU) intralesional injections were found to achieve comparable outcomes when administered alone, although 5-FU was more frequently associated with side effects. Conversely, the combination of 5-FU and TAC was more effective and showed fewer undesirable effects compared to TAC or 5-FU alone. Further options such as needle-less intraepidermal drug delivery are being explored, but more studies are needed to establish safety, feasibility and effectiveness of this approach.
| 66 |
Author(s):
Prof. Debabrata Sahoo, Prof. Debasish Rout, Dr. Ajit Narayan Mohanty, Dr. Somabhusana Janakiballav Mishra.
Page No : 1-7
|
Smelting Strength, Smarter HR: Reinventing Steel Workforce Resilience and Strengthening Economic Turbulence where Industry 4.0 Meets HR Tech
Abstract
The steel industry, a cornerstone of global manufacturing, grapples with significant human resource (HR) challenges amid economic volatility, including supply chain disruptions, raw material price fluctuations, and shifting demand. This study investigates how digital HR platforms—encompassing cloud-based HR information systems (HRIS), virtual training modules, and advanced data analytics—enhance workforce resilience in the steel sector. Using Hyundai Steel, a global steel manufacturer employing more than 10,000 workers, as a case study, the research demonstrates that digital HR solutions yielded a 20% increase in employee adaptability scores, a 15% rise in retention rates, and a 10% improvement in morale, as measured by surveys and key performance indicators (KPIs). A mixed-methods approach, integrating surveys of 250 employees and 60 HR managers, interviews with 25 stakeholders, and statistical analysis via SPSS, provides robust evidence of digital HR’s efficacy. The findings highlight how these platforms enable rapid reskilling, flexible workforce management, and enhanced employee engagement, while addressing barriers such as technological unfamiliarity and resistance to change. This study contributes to the sparse literature on digital HR applications in heavy industries, offering practical strategies for steel firms to bolster resilience and theoretical insights through Resilience Theory and the Technology Acceptance Model (TAM). It underscores digital HR’s pivotal role in fostering a resilient workforce capable of thriving in the dynamic landscape of Industry 4.0.
| 67 |
Author(s):
Kavya s.
Page No : 1-7
|
A study on employee wellbeing with reference to proconnect supply chain solutions
Abstract
This study explores the relationship between employee wellbeing and various factors such as job satisfaction, work environment, salary and compensation, and employee benefits. By identifying the key contributors to employee wellbeing, this research aims to offer valuable insights into enhancing employee wellbeing, and improving organizational efficiency. The objective of this study is to analyses physical, mental & emotional, social, and financial wellbeing among employees at ProConnect. A structured questionnaire was designed and administered to 200 employees.
| 68 |
Author(s):
Keerthana T.
Page No : 1-7
|
HR IN MANAGING CROSS CULTURE DIVERSITY: A CASE STUDY ON DELPHI-TVS TECHNOLOGIES LIMITED
Abstract
This study has been enriched in “DELPHI-TVS TECHNOLOGIES LIMITED” to identify the HR managing cross-culture diversity. HR managing cross-cultural diversity refers to the strategic practices that human resources implement to create an inclusive environment accommodating employees from different cultural backgrounds, thereby enhancing organizational effectiveness and collaboration. Workplace cross-cultural diversity includes a broad range of distinctions, language, religion, and cultural norms. Although diversity can foster creativity, problem-solving, and employee involvement, it also presents particular difficulties like misunderstandings, prejudices, and possible conflicts.
| 69 |
Author(s):
Hemanathan M.
Page No : 1-7
|
EMPLOYEE HEALTH AND SAFETY IN WORK PLACE WITH REFERENCE TO VERSUNI INDIA HOME SOLUTIONS LIMITED
Abstract
This project, conducted at Versuni India Home Solutions Ltd. (formerly Philips Domestic Appliances), aims to enhance workplace health and safety standards within the company's operational environment. The core objective is to assess existing health and safety practices, identify gaps, and implement strategies that align with statutory requirements and best industry practices. By focusing on hazard identification, risk assessment, and the development of control measures, the project seeks to reduce workplace incidents and foster a culture of proactive safety management. Through employee training programs, safety audits, and the implementation of personal protective equipment (PPE) protocols, this initiative emphasizes the importance of employee well-being as a critical component of organizational success. Ultimately, this project contributes to sustaining a safe, healthy, and productive workforce in alignment with Versuni’s commitment to operational excellence and corporate responsibility.
| 70 |
Author(s):
Homam ElTaj.
Page No : 1-7
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DETECTING MALICIOUS URLS: TRENDS, CHALLENGES, AND THE ROLE OF BROWSER EXTENSIONS
Abstract
Malicious URLs continue to pose a significant cybersecurity threat, frequently bypassing conventional detection systems through URL masking and rapid domain switching. This paper proposes a conceptual framework for a lightweight, real-time browser extension designed to block harmful URLs using a dynamically updated blacklist. Beyond detection, the system integrates a user-awareness module offering contextual security guidance and regulatory resources, promoting safer online behavior. The proposed extension aims to address key limitations in existing tools by offering client-side protection with minimal performance overhead and a community driven reporting mechanism. Although the current design employs deterministic logic, future development will incorporate machine learning to enhance adaptability and improve classification of emerging threats. By combining real-time detection, user education, and planned AI integration, the proposed solution contributes a practical and forward-looking approach to strengthening browser level web security.
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Author(s):
aaryamann relan.
Page No : 1-7
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Contextual Framework of Geo Political Factors on World Trade and Commerce
Abstract
The geopolitical landscape plays a crucial role in shaping global trade and commerce. This paper explores the contextual framework of geopolitical factors—including political stability, international relations, strategic alliances, trade wars, and sanctions—and their impact on the global economic order. It delves into how power dynamics between nations influence trade routes, investment flows, supply chains, and access to resources. By examining historical trends and contemporary events such as the U.S.-China trade conflict, the Russia-Ukraine war, and tensions in the Indo-Pacific, this study highlights the interplay between geopolitics and economic interests. The framework presented aims to provide a structured understanding of how geopolitical shifts create both opportunities and vulnerabilities for nations and corporations engaged in international commerce.
| 72 |
Author(s):
Yamini kaushik, Thounaojam Inunganbi, Ms.Anushka.
Page No : 1-8
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BRANDING AND ITS EFFECTS ON CONSUMER BUYING BEHAVIOUR IN RELATION TO THE FASHION INDUSTRY”
Abstract
Brand reputation refers to the overall qualitative assessments and perceived status based on a brand's ability to meet stakeholder expectations. Brand image, on the other hand, encompasses the beliefs, ideas, and impressions that consumers hold about a brand. Previous research suggests both constructs are critical drivers of purchase intentions. However, there is limited understanding of how they impact the conversion of intentions into real purchase behaviours. This study conducts a quantitative survey among consumers to examine how branding affects consumer purchasing decisions in the fashion sector. The findings provide valuable implications for branding strategy by revealing the relative impact of reputation and image dimensions on the various stages of consumer decision-making. From a theoretical standpoint, this research adds to the branding literature by clarifying the roles of reputation and image in driving consumers purchase decision. For marketing practitioners, it offers guidance on prioritizing branding investments to most effectively acquire and retain customers throughout their decision journey and ascribed status based on a brand's perceived ability to meet stakeholder expectations. Prior research suggests both constructs are critical drivers of purchase intentions. However, there is limited understanding of how they affect the consumers decision making while purchasing a fashion accessories.
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Author(s):
Amit Sethi.
Page No : 1-8
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Barriers to Adopting Sustainable Production Technologies in MSIEs: A Case Study of the Sports Goods Industry.
Abstract
Micro, Small, and Informal Enterprises (MSIEs) play a crucial role in the sports goods industry, yet their implementation of sustainable production technologies remains limited due to various barriers. This study explores the challenges hindering MSIEs in integrating sustainable practices into their production processes, specifically focusing on the sports goods sector. Through a case study approach, the study identifies financial, technological, regulatory, market, and organizational constraints that hinder the transition to environmentally friendly technologies.
The key findings highlight limited access to green financing, high upfront costs of sustainable technologies, and inadequate knowledge and technical expertise as significant hurdles. Additionally, weak regulatory enforcement, lack of customer demand for eco-friendly sports goods, and supply chain inefficiencies further increase these challenges.
This research provides valuable insights into the interplay of internal and external factors affecting MSIEs and recommends targeted interventions such as financial incentives, capacity-building programs, and enhanced regulatory frameworks. Addressing these barriers can enable MSIEs in the sports goods industry to achieve sustainability goals while maintaining competitiveness in an evolving global market.
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Author(s):
Samanyu P B.
Page No : 1-8
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React Js Application for Deceptive Document Security and Real-Time Email Alert
Abstract
Threat intelligence has become an essential component of cybersecurity, as firms confront an increasing number of cyber threats such as malware, phishing, and insider attacks. Proactive efforts to detect and prevent breaches before they do major harm have become critical to ensuring data security and operational integrity. Traditional security approaches are no longer sufficient to combat emerging cybercrime tactics, necessitating the use of new detection techniques.
Files are intended to impersonate important assets, deceiving attackers into interacting with them. When attackers interact with these false documents, they unintentionally betray their tools, strategies, and goals. This enables enterprises to obtain essential intelligence about the nature of the threat while protecting their actual assets from compromise.
The purpose of this project is to create and install honey papers that can be used as both decoys and monitoring instruments. By embedding tracking capabilities into these papers, the system can detect unwanted access early on and gain significant insights into attacker activity. This proactive strategy closes gaps in traditional security, strengthening overall defense mechanisms and allowing for faster reactions to incoming threats.
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Author(s):
BHUVANESWARI S.
Page No : 1-8
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A STUDY ON EFFECTIVENESS OF HRIS ON ORGANISATIONAL PRODUCTIVELY WITH REFERENCE TO KOMASTU INDIA PVT LTD
Abstract
A human resource information system (HRIS) is a systematic procedure for collecting, storing, retrieving, and maintaining data that an organization needs concerning the actions of its works, the characteristics of its organizational units, and its human resources. A Human Resources Information system, or HRIS, is a software solution that is used to collect manage ,store , and process an organization‘s employee information Essentially, HR teams use an HRIS to work more efficiently and make more data-driven decisions.. Studying the role of HRIS (Human Resource Information System) in organizations involves exploring how these systems streamline HR processes. Key aspects include their impact on recruitment, employee data management, performance evaluation, and strategic decision- making. Additionally, HRIS's role in enhancing employee engagement, compliance with regulations, and overall organizational efficiency is crucial to examine. The study may also delve into challenges such as implementation issues and the evolving landscape of HR technology. The role of Human Resource Information Systems (HRIS) in an organization is pivotal in modernizing and optimizing human resource management. As organizations strive for efficiency and strategic alignment in their HR functions, HRIS serves as a critical tool in achieving these goals. By integrating various HR processes into a single, cohesive system, HRIS streamlines operations, enhances data accuracy, and provides valuable insights for strategic decision-making. It supports key functions such as payroll management, recruitment, performance tracking, and employee development, while also ensuring compliance with regulations and enhancing data security. Additionally, HRIS empowers employees through self-service portals, improves communication, and facilitates better workforce planning and management. Overall, HRIS not only improves operational efficiency but also contributes to organizational effectiveness by enabling a data-driven approach to human resource management.
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Author(s):
VARSHINI S.
Page No : 1-8
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An Analysis on Core Concepts of Financial Models
Abstract
Financial models serve as the backbone of investment decisions, providing a framework for
evaluating opportunities and managing risk. At the heart of these models lie several core concepts
that are crucial for accurate financial forecasting and analysis. The time value of money, for
instance, is a fundamental principle that recognizes the difference in value between a dollar today
and a dollar in the future. Risk and return are also inextricably linked, with higher returns typically
requiring greater risk tolerance. Discounted cash flow analysis is another essential tool, enabling
investors to estimate the present value of future cash flows and make informed decisions about
investments.
The capital asset pricing model (CAPM) and option pricing models, such as the Black-Scholes
model, are also vital components of financial modeling. These models help investors understand
the relationship between risk and return, and make informed decisions about investments in stocks,
bonds, and other securities. Portfolio optimization is another key concept, involving the selection
of a mix of assets that balances risk and return to achieve an investor's goals.
By mastering these core concepts, investors and financial professionals can develop more effective
investment strategies and make better decisions. Whether evaluating investment opportunities,
managing risk, or optimizing portfolios, a deep understanding of financial models and their
underlying principles is essential for success in today's complex financial markets
| 77 |
Author(s):
GEETHA.S.
Page No : 1-8
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A STUDY ON EMPLOYEE RELATIONSHIP MANAGEMENT WITH REFERENCE TO RK INDUSTRIES
Abstract
Employee Relationship Management is the important factor that lies in the current competitive organization. This relationship stands on organization communication among all the workers and the management which is the essential part to build a good working community. With respect to the growth of the company and to enhance work performance employee must get feedback in both positive and critical, Appreciation and Gratitude which is necessary. The negativity in the employee employer relation, the management might fail to know the issues with regard to the employees who do not achieve long term achievement in the enterprise. In this current competitive world, the accomplishment of good relationship is based on employee job satisfaction. Employees are treated as assets of the company. The employees must try their level best to adjust with each other and should compromise to the extent. And the employees need to enter the office positively. Observation says that the relationship among the employees goes in a long way in motivating the employees and increases the confidence level and morale of the employees
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Author(s):
K Madhumitha .
Page No : 1-10
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Number Theory and It’s Applications
Abstract
ABSTRACT:
Number the ory is a Branch of Mathematics that focuses on the properties and relationships of integers. It is
one of the oldest and most fundamental areas of mathematics, with roots dating back to ancient times. Number
Theory explores concepts such as prime numbers, divisibility, modular arithmetic, and Diophantine equations.
The applications of number theory are diverse and impact various fields beyond pure mathematics. For
instance, in cryptography, number theory forms the basis for encryption algorithms such as RSA, which relies
on the difficult of factoring large composite numbers into primes. Number theory also plays a crucial role in
coding theory, where it helps design error-corecting codes and efficient data transmission methods.
Additionally, in computer science, algorithms based on number theoretic principles are used in tasks ranging
from primality testing to optimization.
Overall, Number theory not only enriches our understanding of the properties of integers but also underpins
numerous practical applications essential to modern technology and communication. These abstract
underscores the foundational significance and practical application of number theory in contemporary
mathematics.
KEYWORDS
Integer, Prime, GCID, LCM, Reminder, Divisor, Divide, RSA, Cryplography, Algebraic Numnber Theory.
Euclidean Algorithm, Chinese Remainder Theorem, Quadratic Residues, Fermat's Theorems, Number
Theoretic Functions, Diophantine Equations, Congruences, Modular Arithmetic.
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Author(s):
Aasha Shaik.
Page No : 1-10
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CLASSIFICATION OF WINE QUALITY PREDICTION WITH RANDOM FOREST
Abstract
The primary objective of this project is to determine whether a wine is of good or bad quality. Traditionally, wine tasting has relied on human judgment based on sensory perception. However, with the advancement of technology, modern industries are increasingly adopting automated solutions across various domains. Predicting wine quality is particularly challenging because taste remains one of the most complex and least understood human senses. An accurate prediction system can significantly aid in the wine evaluation process, which is currently dominated by subjective assessments from human tasters. Introducing an automated model can enhance both the speed and consistency of quality assessments by serving as a decision support tool. Additionally, incorporating feature selection techniques can help identify the most influential factors affecting wine quality. This insight can guide adjustments in the production process to enhance the final product. In this project, a Random Forest Classifier is employed as the classification model.
| 80 |
Author(s):
Atharv Bhatt.
Page No : 1-10
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Vertical Urbanism in Developing India: A Comparative Case Study of Bhopal and Ahmedabad
Abstract
This study examines vertical urbanism—the strategy of building upward rather than outward—as a response to rapid urbanization and land scarcity in India. It compares two mid-sized cities: Bhopal (the “City of Lakes”) and Ahmedabad (a major industrial and cultural hub). A mixed-methods approach was used, combining extensive literature review, analysis of planning documents and satellite data. Key objectives included assessing how vertical development affects land use, housing affordability, environmental quality, and socio-cultural dynamics in each city. Findings indicate that vertical development can substantially increase built-up area and preserve greenfield land. For instance, increasing density can lead to lower service costs, with water and sanitation services in densely populated areas being 30–50% less expensive than in sprawling regions. Incorporating green building features, such as vertical gardens, helps reduce heat-island effects. Without inclusive policies, high-rise buildings may amplify wealth concentration and socio-economic divides. In Bhopal, it is essential to balance vertical expansion with the preservation of lakes, heritage sites, and water resources. In Ahmedabad, which has experienced rapid population growth (from 2.76 million in 1971 to 7.21 million in 2011), vertical development presents a solution for managing density, but it must also prioritize affordable housing and cultural integrity.
The report concludes that vertical urbanism, when combined with sustainable design practices (like green roofs and mixed-use zoning) and fair policies, can facilitate India's overall urban transformation. Recommendations focus on how each city can pursue vertical growth while improving infrastructure, safeguarding cultural heritage, and enhancing environmental resilience.
| 81 |
Author(s):
RESHMA.T.
Page No : 1-10
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A Study on Organisational Culture with reference to Kaleesuwari Refinery Private Limited
Abstract
Organizational culture is the set of shared values, beliefs, and practices that shape how employees behave and interact within a company. It creates the internal environment that influences how people collaborate, make decisions, and approach their work. A strong culture boosts employee engagement, encourages a positive work atmosphere, and drives productivity. It also plays a key role in defining the company’s identity and guiding its strategies.
| 82 |
Author(s):
GOPIKA D .
Page No : 1-10
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A STUDY ON ORGANIZATION ETHICS
Abstract
Organizational ethics refers to the principles and standards guiding behavior within a business or institution. It encompasses values such as integrity, accountability, this study was implemented the simple random sampling of 150 employees statistics tools such as correction, regression, chi- square and ANOVA the organizational culture and decision-making processes. Ethical practices within organizations promote trust among stakeholders, support compliance with laws and regulations, and contribute to long-term sustainability. This abstract explores the importance of ethical frameworks, the role of leadership in fostering ethical behavior, and the impact of ethics on organizational performance. As global scrutiny and stakeholder expectations rise, the integration of ethics into core business strategies has become essential for maintaining reputation and achieving success
| 83 |
Author(s):
UDIT MUDGAL.
Page No : 1-10
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THE ROLE OF BANKS IN SAFE-GUARDING CONSUMER RIGHTS AGAINST CYBER FRAUDS
Abstract
Abstract
This chapter presents an in-depth analysis of the findings from a qualitative study on cyber fraud in the banking sector, with a focus on regulatory frameworks, accountability, and consumer protection. The data was gathered through extensive literature review and analysis of relevant regulatory documents, offering a comprehensive overview of cyber fraud’s nature, impact, and redress mechanisms across different regions.
The chapter begins by outlining the methodology, which employs a thematic approach to identify recurring patterns and insights. It acknowledges inherent limitations, such as reliance on secondary data, which may limit generalizability, and the global diversity in legal frameworks. Ethical considerations, such as data confidentiality and unbiased analysis, are also emphasized.
The study categorizes cyber fraud into external and internal threats. External threats include phishing, malware attacks, social engineering, and identity theft, while internal fraud stems from insider threats. Phishing emerges as the most prevalent form of attack. The scale of cyber fraud is escalating globally, with alarming statistics from the US, UK, and India highlighting significant financial and reputational losses for both consumers and financial institutions.
An evaluation of regulatory frameworks reveals that while comprehensive laws and policies exist—such as those from central banks and cybersecurity agencies—their effectiveness is hindered by enforcement gaps, resource constraints, and the rapidly evolving nature of cyber threats. Despite guidelines that mandate secure channels for transactions and timely breach reporting, many financial institutions struggle with consistent compliance, particularly smaller banks.
The study assesses the banking sector’s accountability in protecting consumers. It finds that although regulatory policies assign clear responsibilities to banks, challenges such as limited resources, fragmented enforcement, and occasional prioritization of profit over security hinder their effectiveness. Consumer education and transparent communication about risks and incidents are lacking. Moreover, banks often delay in responding to complaints, further eroding trust.
Existing redress mechanisms, including reimbursement, dispute resolution processes, legal avenues, and external arbitration bodies, vary in their accessibility and effectiveness. While some banks offer streamlined redressal systems, inconsistencies and delays remain common. Victims often face challenges in proving fraud or locating perpetrators, especially given the cross-border nature of cybercrime.
The study suggests improvements such as the implementation of standardized metrics to evaluate policy effectiveness, increased inter-agency coordination, and enhanced consumer awareness programs. Alternative dispute resolution (ADR) mechanisms, adoption of advanced cybersecurity technologies like biometrics and AI, and equitable regulatory reforms are also recommended.
In conclusion, the findings emphasize that cyber fraud in banking is a multifaceted and escalating problem that necessitates a holistic and collaborative response. The study calls for a strengthened regulatory framework, improved enforcement, heightened accountability, and better consumer support mechanisms. These measures are vital to safeguarding consumer interests, maintaining trust in the financial system, and adapting to the dynamic cyber threat landscape.
| 84 |
Author(s):
Aarchi Goyal.
Page No : 1-11
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Relationship Between Negative Feedback To Employee Engagement
Abstract
This study explores the nuanced relationship between negative feedback and employee engagement within diverse organizational settings. Utilizing a quantitative methodology, the research surveyed 100 employees across industries such as IT, healthcare, education, and manufacturing. The findings reveal that negative feedback, when delivered constructively and empathetically, can enhance motivation and foster higher engagement levels. Conversely, harsh, frequent, or poorly communicated feedback tends to demotivate employees and diminish their emotional commitment to their roles. Key moderating factors identified include feedback delivery style, perceived fairness, emotional intelligence, and managerial training. The study highlights the importance of cultivating a feedback culture rooted in trust and development-oriented communication, offering actionable recommendations for improving feedback practices to optimize employee engagement.
| 85 |
Author(s):
Uzor Onyia.
Page No : 1-11
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Energy Efficient Buildings in Nigeria: Managerial and Policy Assessment
Abstract
This study explores managerial requirements for optimizing energy-efficient buildings (EEBs) in Nigeria, focusing on policy effectiveness, awareness, and adoption barriers. Quantitative research approach was adopted through online questionnaires which yielded 154 responses which were analyzed with descriptive analysis. The respondents are industrial professionals like architects, building technologists, engineers, estate surveyors, consultants, construction Managers. Our findings indicate that while new and updated policies demonstrate continuous improvement in the energy efficiency sector, implementation varies across different climatic zones. Key barriers to EEB adoption include limited access to financing, sustainability promotion, and occupant well-being concerns. Conversely, impactful awareness, research and development, and public-private partnerships are identified as crucial promoters of EEBs. This study provides insights into the Nigerian energy efficiency sector, highlighting areas for policy refinement and strategic intervention. The research contributes to the development of effective managerial strategies for promoting EEBs in Nigeria and similar contexts.
| 86 |
Author(s):
Ari V Lulla.
Page No : 1-12
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Public Perceptions Of The Mandatory 60% Kannada Language Signage Law In Bengaluru, India
Abstract
This paper provides insights into the public perception of the recent 60% Kannada signage law in Bengaluru, a city in southern India. Kannada is the official language of Karnataka, the state where Bengaluru, the fastest-growing metropolis of India is located.
The creation of India from sovereign states involved the reorganization of territories along linguistic lines resulting in formation of Karnataka, with a majority of Kannada speakers. However with the rising influx of working population from other cities, Bangalore is now linguistically diverse.
The recent signage law, implemented in Karnataka, mandates that all commercial establishments must display their signs with at least 60% of the text in Kannada to reflect the regional linguistic identity. The remaining 40% of the signage can be in English or any other language, allowing for inclusivity and understanding by non-Kannada speakers.
To better answer the question of how this law impacts the diverse Bengaluru community, the paper addresses the history of Karnataka, Kannada, language imposition, contributing events leading up to this law and signage regulations in other states.
Data interpretation of directly collected public responses highlight demographic disparities in opinion, and trace the commonalities of certain variables, further contributing to the objective of this paper.
| 87 |
Author(s):
Anirudh Singh.
Page No : 1-12
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Effect of Generational Differences in the Workplace
Abstract
The present study explores the effect of generational differences on workplace dynamics within Indian organizations. With four distinct generational cohorts—Baby Boomers, Generation X, Millennials, and Generation Z—coexisting in the workforce, organizations face both unique opportunities and complex challenges in areas such as communication, motivation, leadership expectations, and collaboration. The study aims to investigate how these generational traits impact team dynamics, employee engagement, and HR effectiveness.
A mixed-method research approach was adopted, combining quantitative data from 300 employee surveys with qualitative insights from HR interviews and focus group discussions. The data were drawn from five major industries: IT, banking, hospitality, retail, and education. Analysis revealed notable generational gaps in work style preferences, feedback expectations, and learning behaviors. For instance, while Baby Boomers value structure and long-term stability, Gen Z prefers flexibility, real-time feedback, and inclusive leadership.
The study highlights that many organizations still follow uniform HR policies that do not address the diverse expectations of a multigenerational workforce. Communication mismatches, leadership disconnects, and outdated training methods were found to be key pain points. However, the research also identifies areas of synergy, where cross-generational collaboration leads to innovation and stronger team performance.
Based on these findings, the report recommends age-inclusive HR strategies such as reverse mentoring, flexible feedback systems, and modular learning programs. The study concludes that embracing generational diversity through customized workplace practices can enhance employee satisfaction, reduce conflict, and build more resilient and future-ready organizations.
| 88 |
Author(s):
Govar Araz.
Page No : 1-13
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A Study on the Effect of Forensic Auditing on Fraud Prevention
Abstract
This study investigates the effect of forensic auditing on fraud prevention by examining the views and experiences of professionals in the field. The majority of respondents are between 26–45 years old, hold Bachelor’s or Master’s degrees, and have 1 to 6 years of experience—representing early to mid-career professionals with moderate qualifications. Most participants consider themselves knowledgeable about forensic auditing, primarily linking it to ensuring the accuracy of financial statements while acknowledging its broader role in fraud detection and legal compliance. However, there is less agreement on the specific focus areas of forensic auditors, suggesting diverse practices across organizations. Forensic audits are conducted regularly, but the frequency varies. Tools used in audits also differ, with interviews, witness statements, digital tools, and document reviews all playing roles depending on the case. Key challenges include complex financial data analysis and maintaining objectivity. Respondents widely agree that forensic auditing is effective in preventing fraud and supporting corporate governance. Although it is well integrated with functions like compliance and legal, improved collaboration with law enforcement is needed. While opinions vary on the need for specialized training, there is strong support for adopting technologies such as AI and block chain. The study highlights opportunities for growth in training, tools, and inter-agency cooperation.