Volume 14 | Issue 1 |

 Abstract

This article examines the potential of forensic linguistics as a rigorous and innovative method for literary interpretation, situating it within the broader interdisciplinary dialogue between law and literature. While forensic linguistics has traditionally functioned as an analytical tool for legal investigations, addressing authorship attribution, discourse analysis, pragmatic inference, and evidentiary evaluation, its methodological principles offer valuable insights into the structure and meaning of literary texts. The study argues that literary narratives, much like legal testimonies, operate as sites of communicative acts shaped by intention, credibility, deception, and power. By applying forensic linguistic techniques to narrative voice, character interaction, stylistic patterning, and discursive structures, the article demonstrates how linguistic evidence can illuminate concealed motives, latent power hierarchies, and the mechanics of narrative reliability. The methodological framework developed here incorporates authorship analysis, speech act theory, Critical Discourse Analysis, forensic narratology, and corpus-based approaches. The discussion highlights both the strengths of this interdisciplinary synthesis such as enhanced interpretive precision and evidentiary rigor, and its limitations, including risks of overinterpretation and challenges related to literary intentionality. Ultimately, the article positions forensic linguistics as a viable and theoretically rich approach that expands the analytical possibilities for contemporary literary scholarship.

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 Keywords

Forensic Linguistics, Literary Interpretation, Discourse Analysis, Forensic Narratology, Law and Literature

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In the modern digital era, effective communication remains a significant challenge for individuals with hearing and speech impairments. Traditional sign language communication often requires trained interpreters, which limits accessibility and real-time interaction with the general population. Although several assistive technologies have been developed, many existing solutions suffer from limited accuracy, lack real-time processing, dependency on internet connectivity, and poor user adaptability. This paper proposes an AI Based Sign Language Recognition and Language Translator designed to bridge the communication gap between sign language users and non-signers. The proposed system utilizes computer vision and deep learning techniques to recognize hand gestures captured through a webcam and convert them into meaningful text and speech in real time. MediaPipe Hand Tracking is employed to extract hand landmark features, which are classified using a custom-trained neural network model. To improve reliability, a confidence-based filtering mechanism is implemented to reduce misclassification of gestures. Additionally, the system integrates an offline speech-to-text module and a multilingual translation component, enabling seamless bidirectional communication across different languages. A Streamlit-based interactive user interface provides real-time visualization, gesture training support, and smooth user interaction. The proposed solution offers a lightweight, scalable, and practical approach for assistive communication, accessibility technologies, and inclusive educational environments.

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 Keywords

Artificial Intelligence, Sign Language Recognition, Hand Gesture Recognition, Deep Learning, Computer Vision, Assistive Technology, Accessibility Systems.

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Agriculture plays a crucial role in the process of economic development of developing countries, as a basic industry. Without achieving substantial increase in agricultural production, no country has moved to the takeoff stage of economic development. In the determination of agricultural labour wages also agricultural production has been playing a prominent role. In emphasizing the role of the agriculture in the development of Indian economy, it is observed, "if one sector limits to growth of the other, it is more likely to be a case of agricultural growth, limiting non-agricultural sector than vice-versa. Ananthapuramu district is no exemption from this. Though there were number of studies on the agricultural sector of the district, this type of studies, 'trends in and determinants of agricultural productivity' are very rare and it helps to successful implementation of several programs to improve the agricultural productivity in the district. To study the 'trends in and determinants of agricultural productivity' simple and multiple regression equations were adopted respectively. A positively significant increasing trend was found in agricultural productivity. In view of determinants of agricultural productivity, it was found that it may increase the agricultural productivity by increasing certain variables which are positively associated with agricultural productivity in the district.

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 Keywords

Agricultural, Productivity, Economic development, Economic Growth, Dependent / Independence Variables

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The integration of artificial intelligence (AI) into language education has introduced new possibilities for improving learner engagement, personalization, and communication skills. Recent studies highlight the growing role of AI technologies such as natural language processing, intelligent tutoring systems, conversational agents, and speech-based feedback in enhancing second and foreign language learning. In parallel, mobile-assisted language learning has emerged as an effective approach for providing flexible, accessible, and self-directed learning environments. However, existing systems often face challenges related to limited interaction, insufficient personalization, and inadequate support for real-time language practice. This paper presents Spokina, an AI-powered mobile language learning application designed to address these challenges through intelligent interaction and adaptive learning support. The proposed system integrates NLP-driven text analysis with a mobile-first architecture developed using Flutter, a backend framework based on CodeIgniter, and a MySQL database for learner data management. Spokina aims to support language acquisition by enabling interactive practice, contextual feedback, and continuous learner engagement within a scalable and user-friendly platform. By combining AI-driven language processing with principles of mobile and digital learning, the system seeks to enhance speaking confidence, learning autonomy, and accessibility. The study demonstrates the potential of AI-enabled mobile applications to complement traditional language learning methods and contribute to more inclusive and effective language education.

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 Keywords

Artificial Intelligence, Language Learning, Natural Language Processing, Mobile-Assisted Language Learning, Educational Technology, Adaptive Learning Systems, Digital Learning, Speech-Based Interaction

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Mental health can be regarded as an onset for every human being in this world. Basically, mental health implies a free mental condition of an individual. Rural women's mental health must be prioritized. gender disparities leave women and their health needs at the margins during health emergencies. There are already existing inequalities in terms of gender based roles, economic insecurity, food insecurity, gender based violence, household and work pressure and unequal access to repercussions on the physical and mental health of women. overall, it found a very high level of mental stress among the rural women, predominantly due to economic and health covers that found women experienced greater mental stress, possibly explained by the additional social pressures they face when all family members are at home. Food insecurity and limited nutritional intake are often limited by financial resources, which have a strong correlation with physical and mental well being. The women in rural areas are more sufferers of mental health problems, and some factors follow many traditional rules, regulations and superstitious beliefs as the majority of women suffer from mental anxieties unknowingly.

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Mental health, Physical health, Gender Inequality, Rural Women

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As India approaches the completion of one hundred years of independence in 2047, the vision of Viksit Bharat, a 30 trillion-dollar goal has emerged as an important policy framework aimed at guiding the country toward developed-nation status. This study examines India's preparedness for this transition by analysing its current economic, social, and institutional conditions in relation to widely accepted development indicators. The analysis is based on secondary data collected from various websites, government publications, international reports, and existing academic literature. Key indicators considered include per capita income, human development, healthcare, education, infrastructure, governance, and environmental sustainability. The findings highlight India's progress in areas such as economic growth, digital expansion, infrastructure development, and social welfare initiatives during the Amrit Kaal period. However, the study also identifies persistent challenges, including income inequality, employment constraints, skill mismatches, regional disparities, environmental stress, and governance-related limitations.

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Amrit Kaal, Atmanirbhar Bharat, HDI, Make in India, NEP 2020, Per Capita GDP, Start up India, Viksit Bharat

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This study uses a semiconductor optical amplifier (SOA) and fibre Bragg gratings to demonstrate an economical and energy-efficient hybrid W/TDM-PON. By providing 10 Gb/s and 1 Gb/s data rates per ONU, system load is managed and a Resource application on demand operation is made possible. The network has a capacity of 80 Gb/s upstream and 160 Gb/s downstream. By just turning on the necessary 10 Gb/s transmitters and using 1 Gb/s transmitters when greater speeds are not needed, energy usage may be decreased. Four-wave mixing in the SOA generates upstream wavelengths, and even in the event of transmitter or receiver failure, the system continues to function. The Q-factor and BER are used to compare the performance of SOA and EDFA.

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SOA, FBG, EDFA, ONU, W/TDM-PON

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A STUDY TO ASSESS KNOWLEDGE REGARDING THE IMPACT OF MOBILE PHONE ON EXAM PERFORMANCE AMONG JUNIOR COLLEGES STUDENTS IN SELECTED COLLEGE OF NAGPUR CITY

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Right Behind You, a novel by Gail Giles, a description of psychosocial development in a young delinquent who is traumatized by feelings of guilt and critique of society is given. This paper describes a sequence of stages in a protagonist from denial and a lack of responsibility to moral thinking and self-acceptance in regard to Identity versus Role Confusion, a stage of Erikson's Psychosocial Development. Kip McFarland, renamed Wade, he is the protagonist of the novel Right Behind You represents youths looking for an identity because of an inappropriate act in attempting to formulate an identity of himself through a violent life. The findings outline self-discovery as an integration of self-reflection and outside perspective from social views of self-discovery, based on a study of stages of psychosocial development through Erikson theory.

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Young Adult Fiction, Identity Formation, Psychosocial Theory, Moral Development, and Juvenile Offenders.

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This paper examines the multifaceted contribution of Andhra Kesari Tanguturi Prakasam Panthulu to the social development of Andhra. A distinguished lawyer, journalist, freedom fighter, parliamentarian, and administrator, Prakasam Panthulu left a lasting imprint on every sphere of public life he entered. His influence on the social fabric of Andhra was profound and unparalleled. Inspired by Gandhian constructive programmes, he initiated several pioneering reforms aimed at the uplift of Dalits, handloom weavers, and other marginalized sections of society. His rural development initiatives, particularly the Firka Development Programme, later served as a model for the Community Development Projects that transformed rural India.

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THE CONTRIBUTION OF ANDHRA KESARI TANGUTURI PRAKASAM PANTHULU TO THE SOCIAL DEVELOPMENT OF ANDHRA

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