Volume 14 | Issue 4 |

 Abstract

This paper examines the role of Large Language Models (LLMs) in English language teaching through the theoretical lens of Bakhtinian dialogism. Bakhtin's ideas of heteroglossia, polyphony, and dialogic interaction highlight that meaning emerges through the interplay of diverse voices. While the traditional classroom already embodies this multiplicity through teacher-student exchanges and peer dialogue, the arrival of LLMs introduces a new interlocutor, artificial yet dialogically responsive, into the pedagogical arena. LLMs can simulate a wide range of registers, perspectives, and critical positions, creating opportunities for students to engage with multiple "voices" simultaneously. For instance, an LLM may provide feedback as a formalist critic, a peer reviewer, and a language tutor, compelling learners to evaluate, synthesise, and position themselves within a plurality of perspectives. In literature classrooms, LLMs can animate characters or critics, expand interpretive possibilities, and foster a genuinely polyphonic environment. The study employs autoethnography to examine the researchers with LLMs as learners, teachers, and critics. Reflective journaling of AI-human exchanges provides the basis for analysis, capturing both the machine's textual utterances and the researcher's responses. These narratives are read thematically through Bakhtin's framework to explore moments of dialogic expansion where LLMs simulate polyphony by generating multiple voices or perspectives, as well as tensions where the machine's lack of ethical answerability disrupts authentic dialogue. The paper argues that LLMs, when integrated critically, can cultivate dialogic competence, rhetorical agility, and AI literacy, thereby extending Bakhtinian dialogism into the digital age without displacing the ethical centrality of human pedagogy.

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 Keywords

Index Terms: LLM, Bhakthin, Interlocuter, AI, and polyphony.

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ABSTRACT: Background of the study: The IHI developed the "Ventilator Bundle," comprising four evidence-based practices, along with a methodology for implementation and compliance measurement. The study objectives to evaluate nursing officers' knowledge and practices related to ventilator-associated pneumonia (VAP) care. Research methodology: It employs a descriptive quantitative design with a sample of 100 participants selected through non-probability convenient sampling. The research tool consists of three parts: Part 1 covers socio-demographic information, Part 2 is a self-structured questionnaire with 24 items scored from 0 to 1, and Part 3 is a checklist containing 20 items, also scored from 0 to 1.conclusion: A study on ventilator-associated pneumonia (VAP) revealed that 67% of participants had excellent knowledge, 28% good knowledge, and 5% average knowledge. In terms of practices, 55% exhibited good practices, while 40% showed excellent practices, with no participants falling below fair practice levels. Overall, nursing officers implement appropriate VAP care practices.

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Keywords: knowledge, practice, ventilator-associated pneumonia (VAP),bundle of care, nursing officers.

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Electricity theft is one of the most significant problems faced by power distribution companies, leading to substantial financial losses, reduced efficiency, voltage instability, and overloading of distribution networks. Unauthorized tapping, illegal connections, and meter bypassing not only affect revenue generation but also compromise system reliability and public safety. To address this issue, an efficient, low-cost, and automated monitoring solution is required.

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Arduino Uno / Microcontroller GSM Module (SIM800 / SIM900) Power Theft Detection Smart Energy Meter Embedded System Electrical Monitoring System

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Abstract The world has witnessed a commendable new media revolution, expansion of knowledge, and interactive communication. The new media have created virtual communities that have crossed geographical boundaries. Digital, networkable, compressible, and interactive are the basic characteristics of new media technologies. The Internet, in particular, offers the potential for a democratic postmodern public sphere in which citizens can engage in well-informed and non-hierarchical debate about their social structures. India has also made commendable progress in communication science and technology. Policymakers have recognized that active participation of underprivileged, marginalized, underserved, and under-represented segments of society, including women and vulnerable groups, is critical for inclusive development. As society shifts towards a knowledge-based and development-oriented society, the critical role of new media in Dalit empowerment becomes clear. The importance of the media in national development is widely acknowledged by media scholars.

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New Media, Inclusive Development, Empowerment of Dalits.

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In the digital era, data security has become a critical concern due to the exponential growth of data and the increasing sophistication of cyber threats. Traditional centralized systems are often vulnerable to data breaches, unauthorized access, and single points of failure. Blockchain technology has emerged as a promising solution to address these challenges by providing a decentralized, transparent, and tamper-resistant framework for data management. This research paper explores how blockchain technology enhances data security by leveraging cryptographic techniques, distributed consensus mechanisms, and immutable data structures. The study also discusses applications, benefits, limitations, and future directions of blockchain-based security systems.

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Blockchain, Data Security, Cryptography, Decentralization, Immutability, Consensus Mechanisms, Distributed Ledger Technology (DLT).

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Facial Emotion Detection is an important application of computer vision and deep learning that enables machines to recognize human emotions from facial expressions. This paper presents an efficient real-time facial emotion detection system using the ResNet-18 deep convolutional neural network architecture trained on the Extended Cohn-Kanade (CK+) dataset. The proposed system performs face detection using OpenCV Haar Cascade and applies preprocessing techniques such as resizing, normalization, and grayscale conversion before feature extraction. The ResNet-18 model automatically learns discriminative facial features and classifies expressions into seven emotion categories: happy, sad, angry, fear, surprise, disgust, and neutral. The system is capable of predicting emotions from live webcam input with high accuracy and confidence levels. Experimental results demonstrate reliable performance in real-time environments, making the system suitable for applications such as human-computer interaction, smart classrooms, healthcare monitoring, and driver assistance systems. The proposed approach improves classification efficiency while maintaining computational simplicity for practical deployment.

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Facial Emotion Detection, Deep Learning, ResNet-18, Computer Vision, CK+ Dataset, Emotion Classification, OpenCV, Convolutional Neural Networks, Human-Computer Interaction, Real-Time Emotion Recognition

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In today's fast-changing digital economy, Small and Medium Enterprises (SMEs) are increasingly using digital marketing techniques to improve their market presence, customer engagement, and business performance. The different digital marketing tools and techniques used by SMEs, such as social media marketing, search engine optimization (SEO), email marketing, content marketing, and online advertising. The study also investigates the level of awareness, usage, and effectiveness of these digital marketing practices in achieving organizational goals. The study uses both primary and secondary data. The primary data was collected using structured questionnaires among SME owners and marketing managers, while secondary data was collected from journals, reports, websites, and previous studies. Statistical methods such as percentage analysis, graphs, and descriptive analysis were employed to analyze the data. The results show that digital marketing is an important factor in improving brand awareness, customer reach, and sales performance of SMEs. However, factors such as a lack of technical expertise, budget constraints, and limited digital infrastructure are some of the challenges that impede effective implementation. The study concludes that with proper training, planning, and cost-effective digital marketing tools, SMEs can effectively use digital marketing to create a competitive advantage and ensure sustainable growth.

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Digital Marketing, Small and Medium Enterprises (SMEs), Social Media Marketing, Business Performance, Customer Engagement.

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Shiksha Me Hindu Studies Hindu Adhyayan Ki Avashyakta Aur Iska Mahatv

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Shiksha Me Hindu Studies Hindu Adhyayan Ki Avashyakta Aur Iska Mahatv

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This project presents the tribological behavior of silicon oxide (20 nm), ZDDP, and hBN nanoparticle additives in castor vegetable oil to enhance the lubricating performance. The nanoparticles were dispersed in the base oil at different concentrations (0.3%, 0.4%, and 0.6%). The prepared nano-lubricants were evaluated for their physical and tribological properties, including viscosity (using a Redwood viscometer), viscosity index, flash point, fire point, and pour point. The results indicate that the addition of nanoparticles significantly improves lubrication performance by reducing friction coefficient and wear. Surface analysis using scanning electron microscopy (SEM) confirmed the formation of protective films on the worn surfaces, which contributed to improved anti-wear characteristics.

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Friction coefficient, lubricating oil, nanoparticles, wear behavior, SEM analysis

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Emotional Intelligence (EI) is defined as a type of social intelligence that involves the ability to monitor one's own and others emotions, to discriminate among them and to use the information to guide one's thinking and actions. (Mayer & Salovey, 1993). The present study was conducted to evaluate the effect of perceived maternal parenting styles on emotional intelligence among high school students. The sample consists of 100 B.Ed., students 50 male and 50 female students from five B.Ed colleges in Tirupathur district of Tamilnadu. Trait Emotional Intelligence Questionnaire ASF by Petrides et al. (2006) was used to measure emotional intelligence. To measure perceived maternal parenting style, Parenting Scale (P Scale) by Bharadwaj et al. (1998) was used. The parenting styles Rejection vs. Acceptance, Carelessness vs. Protection and Freedom vs. Discipline were taken for the present study. The data was analyzed using one-way ANOVA. It was found that perceived maternal parenting styles such as Rejection vs. Acceptance and Freedom vs. Discipline had a significant influence on emotional intelligence among the sample but the parenting style Carelessness Vs. Protection had no significant influence on the emotional intelligence among the sample. It was also found that the parenting style Rejection vs. Acceptance had a significant influence on emotional intelligence only among the males.

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Emotional Intelligence, Perceived Maternal Parenting Styles.

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