Volume 13 | Issue 4 |

 Abstract

In recent years, social media has emerged as a dominant force in shaping communication, socialization, and even education, particularly among students. With platforms like Instagram, Facebook, YouTube, and WhatsApp widely used by high school and college students, questions arise about the implications of this digital shift on learning outcomes. This study investigates the relationship between social media use and academic performance. A mixed-methods approach was adopted, involving 500 students from both secondary and tertiary institutions. The findings indicate a nuanced impact--while social media can support collaborative learning and resource sharing, excessive and unregulated use is strongly correlated with distraction, procrastination, and lower academic performance. This paper explores these dimensions in detail, offering recommendations for students, educators, and institutions on how to harness social media as a tool for academic enhancement rather than a source of disruption.

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 Keywords

social media, academic performance, learning, digital distraction, education, students, productivity

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Landmines, while effective in securing territories during warfare, pose a significant threat to military personnel even after deployment, often resulting in accidental injuries or fatalities among friendly forces. This research presents the design and implementation of an intelligent [1] RF-based landmine deactivation system aimed at preventing unintended detonations for friendly soldiers while maintaining full functionality against enemy intrusions. The system is divided into two units: a transmitter embedded in the soldier's footwear and a receiver integrated within the landmine. When a friendly soldier, equipped with the RF transmitter, enters the proximity of the landmine, the receiver detects the signal and activates a relay to disconnect the detonation mechanism. In contrast, if an enemy without a valid transmitter approaches and steps on the landmine, the system remains armed and triggers upon pressure activation. The RF communication is facilitated using 434 MHz modules along with HT12E and HT12D encoder-decoder pairs for signal transmission and reception. This low-cost, efficient system demonstrates a selective activation mechanism that significantly enhances battlefield safety for [2] friendly troops. The project lays the groundwork for future integration of encrypted communication, [3] GPS tracking, and centralized control, contributing toward the development of smarter, more humane defense technologies.

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 Keywords

Landmine Deactivation, RF Communication, HT12E Encoder, HT12D Decoder, Soldier Safety, Wireless Transmitter-Receiver System, Relay-Based Switching, Selective Triggering, Embedded Defense Systems, Friendly Force Identification.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper puts forward DecentRaise, an innovative decentralized crowdfunding platform, built on blockchain technology and aimed at overcoming the very basic limitations inherent in centralized crowdfunding. Raising the seed round affords a very unique opportunity to earn money running a project whilst allowing that person to maintain a majority stake in his own company. Our implementation builds with Solidity for smart contracts, React.js for the front-end interface, and IPFS for decentralized file storage. Web3.js has been incorporated in the architecture for blockchain interaction, MetaMask for wallet integration, and ERC-20 Token Standard for the creation of campaign tokens. Key features included an automated milestone-based release mechanism for funds, decentralized voting systems for project governance, and cryptographically verified authenticity for campaigns. Performance analysis shows a shortened cost down of 62 times less than regular ones, higher than other platforms, with a seriously thought secure-level guaranteed by the immutable transaction log, as well as the distributed consensus algorithm. System 99.9% is operationally a highly decentralized unrelated system of hosting, and this hit a meaningfully higher rank of transparency and trust metrics through empirical evaluations.

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 Keywords

Blockchain technology, Ethereum, smart contracts, decentralized applications (dApps), Web3, IPFS, crowdfunding platforms, distributed systems, consensus mechanisms, cryptocurrency

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Music through its auditory nature merges specific structured auditory elements and pauses into arrangements which induce mental wellness in people. Preferred music acts as a mood enhancer before vital occasions and provides soothing relief when emotions run high. It achieves this and more throughout the middle range too. People have long studied and respected music since it functions as a source of healing as well as entertainment. Modern scientific studies demonstrate that music possesses major capabilities which successfully decrease anxiety but also lower stress while enhancing cognitive focus. People commonly observe that slow-tempo music used in meditation helps decrease heart rate and both minimizes stress and anxiety. During Indian yoga meditation practitioners experience musical guidance through speakers who assist them in reaching their flow objectives and defining targets. Listening to music enhances attention while carrying out complex tasks. Listening to music can enhance brain functions for information storage such as memories and mental relationship formation. In this context the main purpose of this study to find out the attitude of higher secondary students towards music on the reduce of stress in West Bengal. Researcher framed Five null hypotheses, 200 students of higher secondary level in Nadia and kolkata district including urban and rural area of west Bengal was considered as sample. In this study, the purposive sampling technique was adopted for sample selection. Researcher developed a tool to measure attitude towards music on the reduce of stress.The validity of the questionnaire was estimated by the expert and content validity has been maintained properly in this study. For reliability measure, test retest method was applied. After collection of data 't' test was applied for testing hypotheses.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Music , Stress , School Education , Mental Health

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Lung cancer is one of the most prevalent and deadly forms of cancer worldwide, primarily due to its late detection and the complexity involved in accurately diagnosing its various subtypes. Early detection and precise classification of lung cancer types are vital for effective treatment and improved patient survival. This research introduces a deep learning-based approach for the automated detection and classification of lung cancer using computed tomography (CT) scan images. Specifically, we utilize the VGG16 Convolutional Neural Network (CNN) architecture, known for its strong image feature extraction capabilities. The proposed model is trained to classify lung CT images into four categories: adenocarcinoma, squamous cell carcinoma, large cell carcinoma, and normal (non-cancerous) tissue. We employed transfer learning to adapt the pre-trained VGG16 model to our medical imaging dataset. The data underwent pre-processing steps such as normalization and augmentation to enhance model performance and reduce overfitting. The results demonstrate that our deep learning model achieves high accuracy and strong performance across multiple evaluation metrics including precision, recall, and F1-score. This validates the effectiveness of CNN-based architectures in supporting radiologists and improving the diagnostic process. The approach shows significant potential in clinical applications for early and automated lung cancer detection, laying the foundation for future enhancements involving larger datasets and model interpretability.

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 Keywords

Lung Cancer, Deep Learning, VGG 16 CNN, CT Scans, Image Processing, Feature Extraction.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Adhatoda vasica (Adulsa) is the main active ingredient of a herbal cough syrup that is being developed and evaluated in this study. Because of its well-established bronchodilatory, expectorant, and anti-inflammatory qualities, Adhatoda vasica is a useful treatment for respiratory conditions. The syrup was made with appropriate additions to improve palatability, stability, and medicinal efficacy, following standard pharmaceutical methods. The prepared syrup was assessed for a number of physicochemical characteristics, such as stability over time, microbiological load, viscosity, pH, and organoleptic qualities. The adulsa-based syrup passed acceptable pharmaceutical standards, according to preliminary data, and showed promise as a natural, efficient remedy for cough and related respiratory conditions.

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 Keywords

Adult formulation, cough syrup, antitussive, expectorant, Guaifenesin, dextromethorphan, and syrup base

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The paper titled Echoes of Silence: A Critical Examination of Women's Struggles in Mahesh Dattani's Dramatic Landscape delves into the complex portrayal of women's issues in the plays of Mahesh Dattani, a prominent Indian playwright. Dattani's works provide a profound exploration of the psychological, social, and emotional struggles faced by women, particularly in the context of contemporary Indian society. Through plays such as Tara, Bravely Fought the Queen, and Final Solutions, Dattani highlights themes of gender inequality, patriarchal control, and the silencing of women's voices. This paper examines how Dattani employs various dramatic techniques, including non-linear narrative structures, symbolic representations, and complex characterisation, to reveal the inner conflicts of female characters. The study also focuses on the intersectionality of gender, caste, and sexuality as explored in his works, illustrating how these factors shape the lives of women. Dattani's portrayal of women is not merely a reflection of their oppression but also a critique of the societal norms that perpetuate their marginalisation. By analysing the various dimensions of women's struggles in Dattani's plays, this paper aims to shed light on the broader socio-cultural implications of his work, offering a critical perspective on the quest for identity, autonomy, and empowerment in the face of silence and repression.

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 Keywords

Women's Struggles, Mahesh Dattani, Gender Inequality, Patriarchy, Empowerment

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 Abstract

The pursuit of equality, as envisioned by Ram Manohar Lohia, is a foundational aspect of his socio-political philosophy. Lohia, an influential Indian freedom fighter, political thinker, and social reformer, emphasized the necessity of economic, social, and cultural equality in shaping a just society. His principles advocated for the empowerment of marginalized groups, particularly those at the intersection of caste, class, and gender disparities. Lohia's critique of the prevailing social structures emphasized the need to address systemic inequalities through affirmative action, decentralization of power, and the promotion of social justice. His belief in the eradication of untouchability, his advocacy for linguistic equality, and his demand for the decolonization of the mind positioned him as a revolutionary thinker in post-independence India. This abstract explores the core tenets of Lohia's thought, analyzing his unique contributions to the discourse on equality, as well as his emphasis on a multi-dimensional approach to achieving social transformation. By synthesizing his ideas on economic democracy, social mobility, and cultural inclusiveness, Lohia's work continues to inspire movements aimed at realizing a truly egalitarian society.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Equality, Empowerment, Social justice, Untouchability, Democracy, Social mobility.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Hyperautomation is transforming the way businesses operate by integrating advanced technologies such as robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), and advanced analytics. Unlike traditional automation, which focuses on automating individual tasks or processes, hyperautomation adopts a more comprehensive approach, enabling the automation of complex workflows from start to finish. This integration of technologies allows organizations to streamline operations, minimize manual intervention, and enhance decision-making by leveraging data-driven insights. The holistic nature of hyperautomation lies in its ability to combine multiple tools and technologies to address both structured and unstructured processes. By doing so, it not only optimizes efficiency but also creates scalable systems that adapt to evolving business needs. Moreover, hyperautomation enhances agility by enabling faster responses to change in the market or internal processes, making it a critical asset for organizations striving to stay competitive in the digital age. This approach ensures that businesses can maximize operational efficiency while minimizing costs and resource usage.

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 Keywords

Hyperautomation, Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Advanced Analytics, Workflow Automation, Digital Transformation, Process Optimization, Operational Efficiency, Data-Driven Decision Making, Business Agility, Unstructured Data Automation, End-to-End Automation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In financial engineering, stock market prediction is a crucial subject, particularly given the ongoing advancement of innovative methods and strategies in this area. In this study, we look into how sentiment exhibited in Twitter tweets affects the ability to predict stock prices. Twitter is the social networking site that gives everyone a free forum to publicly share their opinions. In specifically, we use the API to retrieve the company's live Twitter tweets. Every special character and stop word in the dataset is taken out. The Random Forest classifier is used to analyze sentiment in the filtered data. As a result, the tweets are categorized as neutral, negative, and positive. To get the outcome, the machine learning model receives the stock data and the tweet data as input. The stock market price is predicted using the ML classifier as a model. The real stock market value is contrasted with the predicted value that was obtained. Experiments employing real-time Twitter data and daily stock data from a number of businesses. The project's objective is to forecast the future price of a stock of interest by combining sentiment analysis of news headlines and Twitter tweets with previous stock data.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Stock Market, Data Analysis, Machine Learning, Stock price Prediction, Social Media.

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Creative Commons Attribution 4.0 and The Open Definition