Volume 13 | Issue 3 |

 Abstract

Teachers are perhaps the most significant members of our society. They inspire, nurture dreams, shape personalities, spread knowledge and enhance human potential. In the 21st century, teacher's role has gone much beyond teaching. They play multifarious role which often leads emotional exhaustion, reduced personal accomplishment, and stress among teachers, which negatively impact their academic performance and personal lives (Tripathi, P. 2024). Teachers being the pillars of the nation have to continue to shoulder the responsibilities but also need to cope with the adversities in the educational setting at the same time. Resilience is commonly considered a desirable quality, a core strength to positively influence one's performance, academic achievement, well-being and health (Bartley, et. Al, 2010. Martin & Marsh, 2009). The aim of this paper was to study the impact of positive education program on academic resilience of pre- service teachers. The quasi experimental design of the one group pre-test post-test type is used. The tool used to collect data was Academic Resilience Scale (D'souza and Pandya, 2017). Data was collected from 30 student teachers. T-test was used to compare the pre- test and post- test scores of the experimental group. The findings of the study reveal that the post- test scores on Academic Resilience of pre-service teachers from the experimental group is higher than the pre-test scores. This positive effect on Academic Resilience scores of pre- service teachers can be attributed to the positive education programme which led to the development of academic resilience in pre-service teachers.

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 Keywords

Academic Resilience, Positive Education Programme, Student- teachers

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The increasing complexity of digital documents demands innovative tools to enhance accessibility and comprehension. This paper presents the Intelligent SmartDoc Chat Assistant , an AI-powered solution designed to transform user interactions with PDF documents. Built using modern technologies such as React, TypeScript, Node.js, TRPC, and Prisma , the system provides an intuitive interface and robust data management. The assistant integrates NVIDIA Llama-3.1-Nemotron-70B-Instruct, a state-of-the-art AI model, to deliver real-time, context-aware responses. By leveraging natural language processing (NLP) and large language models (LLMs) , users can ask questions, navigate document sections, and gain insights effortlessly. This dynamic question-answering capability, combined with context-aware suggestions, enhances productivity across industries like education, law, and business. Unlike traditional PDF readers, which limit interaction, the SmartDoc Assistant offers a natural and interactive approach, addressing user frustration and disengagement in static document environments. It bridges the gap between static formats and dynamic interactions, providing advanced document analysis and seamless communication. Designed for scalability, accuracy, and efficiency, the SmartDoc Assistant supports diverse applications, including legal research, academic analysis, and business documentation. By simplifying workflows and offering intelligent solutions, it has become an essential tool for professionals and everyday users alike.

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 Keywords

Intelligent assistant, AI-powered document interaction, Natural language processing (NLP), Large Language Models (LLMs), PDF document analysis, Smart document assistant, React, TypeScript, Node.js, Real-time insights, Context-aware responses, Document management solutions.

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Creative Commons Attribution 4.0 and The Open Definition

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 Keywords

Prediction of heart disease, Voting Classifier, Machine Learning, Flask framework, Ensemble Learning, Secure Authentication, Real-time Testing, CVD.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the modern academic environment, access to information is a crucial factor in research productivity and knowledge acquisition. This study examines the information access patterns of users in selected affiliated colleges under Madras University Libraries. It focuses on the prevalence of digital resource usage, the mechanisms employed for information retrieval, and the challenges faced by users in accessing scholarly content. The findings reveal a strong preference for electronic sources over traditional library resources. Wikipedia (81.75%) and online databases (74.45%) are the most frequently used digital resources, particularly among students. Faculty members, on the other hand, rely more on subject gateways, institutional databases, and citation indexes. The study also highlights gender-based differences in digital resource utilization, with male respondents engaging more actively in online research than females. Despite the widespread use of digital platforms, several challenges hinder efficient access to scholarly materials. These include limited digital literacy skills, slow internet connectivity, restricted access to paid journal subscriptions, and inadequate library support. Addressing these issues requires targeted digital literacy programs, enhanced access to subscription-based databases, and institutional investments in library infrastructure. The study concludes that universities must prioritize digital literacy training, expand research database subscriptions, and promote open-access resources to bridge the information access gap. These strategies will ensure that students, faculty, and researchers maximize the potential of digital academic resources for improved research outcomes.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Information Access - Digital Literacy - Academic Search Behavior - University Libraries - Electronic Resources

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Creative Commons Attribution 4.0 and The Open Definition

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This project deals with the design of new products. In recent years, floor cleaning and fabrication of manually operated floor cleaning machine. The conventional floor cleaning and machines is most widely used in airport platforms, railway platforms, hospitals, bus stands, malls and in many other commercial places. These devices need an electrical energy for its operation not user friendly. In India, especially in summer, there is power crisis and most of the floor cleaning machine is not used effectively due to this problem, particularly in bus stands. Hence it is a need to develop low cost, user friendly floor cleaning machine. In this project, an effort has been. made to develop a manually operated floor cleaning machine so that it can be an alternative for conventional floor cleaning analysis of the floor cleaning machine was done using suitable commercially available software. The conventionally used materials were, considered for the components of floor cleaning machine.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Floor cleaning machine, Design and Fabrication, Analysis.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Facial recognition technology has gained widespread adoption due to its non intrusive and user-friendly characteristics, making it a cornerstone in security and authentication systems. However, its growing prevalence has exposed significant vulnerabilities to spoofing attacks, where adversaries employ counterfeit biometric data-- such as printed photographs, video replays, or 3D masks--to bypass authentication mechanisms. This study presents a real-time face spoofing detection system powered by MobileNetV2, a lightweight convolutional neural network pre-trained on ImageNet and finetuned to distinguish genuine faces from spoofed ones. The system excels at detecting subtle texture and pattern anomalies, imperceptible to human observation, that signal spoofing attempts. To ensure robustness, data augmentation techniques replicate diverse real-world conditions, enhancing the model's generalization. Implemented with computational efficiency in mind, the system supports real-time deployment. Evaluation on the LCC-FASD dataset demonstrates high accuracy and reliability, validating its effectiveness. By bolstering the resilience of facial recognition systems against spoofing, this solution significantly enhances security across applications requiring dependable biometric authentication.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Face Spoofing Detection, MobileNetV2, Real-Time Detection, Convolutional Neural Networks, Liveness Detection, Security Enhancement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This review looks at the complex relationship between cosmetics and acne, showing the positive and negative consequences of different cosmetic chemicals and products. We go over the pathophysiology of acne, cosmetic dermatology, and tips for acne-prone people.

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 Keywords

Acne, acne-causing and acne-fighting cosmetic components,Cosmatics therapies.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Fast-Moving Consumer Goods (FMCG) sector is one of the largest and most competitive industries in India, significantly contributing to economic growth and employment. Hindustan Unilever Limited (HUL), a market leader in this sector, has a strong presence across urban and rural markets. This study aims to analyze consumer behavior in the FMCG industry, focusing on the factors that influence purchasing decisions, such as brand image, price, product quality, user recommendations, taste, and advertising. It also evaluates consumer satisfaction levels with HUL products and explores how marketing strategies impact brand loyalty and purchase behavior. The study further examines the role of advertisements in shaping consumer perceptions and the challenges consumers face in selecting FMCG products amidst a wide array of choices. Additionally, it investigates how changing consumer preferences have led to modifications in the marketing mix, compelling companies like HUL to adopt innovative strategies to stay competitive. By providing insights into the effectiveness of HUL's marketing initiatives and consumer engagement, this research aims to help businesses refine their approaches to better cater to customer needs and enhance brand loyalty in an evolving marketplace.. Key words : FMCG Industry, Consumer Behaviour and Purchasing Decisions

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Creative Commons Attribution 4.0 and The Open Definition

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FMCG Industry, Consumer Behaviour and Purchasing Decisions.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The main cause of death worldwide is heart disease, so we must have accurate models to help diagnose and assess the risk of heart disease early on. The research focuses on predicting heart disease using categorical learning algorithms, CatBoost, and Multilayer Perceptrons. and Random Forest (RF). The preprocessed and class balanced dataset of 2,659 samples was employed to train, validate and test the models. Performance measurement indicated Random Forest to be the most accurate (94.18% testing, 97.93% validation) followed by CatBoost (92.71% testing, 92.71% validation) and MLP (93.65% testing, 95.31% validation). Risk assessment was incorporated into the prediction and patients were sorted into high, medium and low risk categories. The most relevant predictors were chest pain (28%), ST depression (24%) and ECG features (15%). Confusion matrix analysis revealed that CatBoost reduced false negatives so it's the most appropriate for identifying heart disease cases. Random Forest's ensemble method was more suitable for generalization so it's the best for predictive accuracy. The findings reveal the significance of machine learning in early detection of heart disease and has implications for clinical decision support and personalized risk management.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Heart Disease Prediction, Machine Learning, Model Evaluation, Risk Assessment, Risk Factors.

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Creative Commons Attribution 4.0 and The Open Definition

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The research paper examines the impact of Gender Sensitization training for candidates undergoing pre sea and post sea competency courses in Training Ship Rahaman. Gender Sensitization training has become crucial to addressing biases, fostering mutual respect, and creating a more inclusive environment for all. Gender sensitivity is a concept that aims to remove the barriers created by discrimination and gender prejudice. Creating a gender-sensitive setting fosters mutual understanding among people of all genders. This course will focus on addressing key concerns and bring about thought and conversation on aspects that will be critical to gender sensitization in the maritime industry. Less than 1.28% of seafarers are women (as per BIMCO/ICS 2021 Seafarer Workforce Report) and much can be done to increase this percentage to a healthier balance. In India, we are still evolving and currently women seafarers represent only 0.7% of active Indian seafarers. (Directorate General of Shipping, 2023)

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gender Sensitization, Maritime, Women, Empower, Training.

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Creative Commons Attribution 4.0 and The Open Definition