Volume 14 | Issue 6 |

 Abstract

Inclusive education succeeds when teaching adapts to the learner rather than expecting the learner to adapt the system. By creating responsive and learner centered classrooms, schools can create responsible citizens. There is dire need to make the teaching and learning more interesting and involving .It is the responsibility of the educators to bring about innovative styles of teaching in order to reduce the dropout rates . Moreover, there should be a blend of traditional and modern teaching strategies so that educators can promote inclusivity in the classroom. This study has been divided into three sections. Section I deals with the introduction stating the need of adaptive steps for better dissemination of knowledge. Section II states the different strategies and techniques to make teaching and learning more interactive, exciting and involving. Section III states the conclusion and future prospectus of the study

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KeyWords: Inclusive Education, Dropout rates, Innovative styles,Educators, Adaptive

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Generative artificial intelligence technology has allowed for the creation of highly realistic synthetic videos called "deepfakes." Deepfakes offer a way to enhance many different uses of media; however, they are also responsible for major problems like misinformation, identity theft, and threats to digital security [1],[2]. Consequently, it is challenging for computer vision methods to differentiate between real and deepfake videos. This paper presents a deep learning framework based on a spatio-temporal approach to identify AI-generated deepfake videos. The spatio-temporal approach includes video preprocessing to retrieve video frames, detect and normalize faces in those frames, and then use convolutional neural networks (CNN) to retrieve spatial features from those normal faces. After retrieving the spatial features from the video frames, the video frames are analyzed for temporal inconsistencies between frame relationships to increase detection accuracy [3],[4]. The detection system is created using a web application developed using Flask, allowing real-time video analysis. The experimental results of this research show that the proposed system exhibits constant improvement (as indicated by reduced loss and increased accuracy) until a steady state is achieved as training progresses. Therefore, the proposed deepfake detection system will show accurate results and provide the computational efficiency required for deployment in a real-world context.

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 Keywords

Deepfake, AI-generated video, AI, CNN, spatio-temporal detection, computer vision, automated video classification.

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The essay has emerged as a significant literary medium through which philosophical ideas are expressed in accessible and reflective forms. This paper examines how philosophy is articulated through literary prose in the essays of G. K. Chesterton and S. Radhakrishnan, focusing on form, style, and expressive method rather than comprehensive philosophical systems. Situated within the shifting boundaries between philosophy and literature, the study highlights how the essay functions as a bridge between abstract thought and lived human experience. G. K. Chesterton's use of paradox, imagination, and everyday language demonstrates how philosophical insight can arise from common experience, while S. Radhakrishnan's reflective and interpretative prose reveals the capacity of the essay to synthesize spiritual and ethical ideas with clarity and seriousness. Through a comparative literary analysis, the paper argues that both writers democratize philosophy by addressing the general reader and engaging moral and spiritual concerns through accessible prose. The study contributes to English literary and comparative studies by foregrounding the essay as a vital form of philosophical expression and by illustrating how Eastern and Western traditions converge in valuing literature as a medium of ethical and intellectual inquiry.

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Key words: Essay as Philosophy, Literary Expression, Comparative Ethics

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A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURE TEACHING PROGRAMME ON KNOWLEDGE REGARDING CALCIUM DEFICIENCY DISORDERS AMONG POSTMENOPAUSAL WOMEN IN A SELECTED AREA OF MEHSANA CITY, GUJARAT

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A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURE TEACHING PROGRAMME ON KNOWLEDGE REGARDING CALCIUM DEFICIENCY DISORDERS AMONG POSTMENOPAUSAL WOMEN IN A SELECTED AREA OF MEHSANA CITY, GUJARAT

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Among the percussion instruments of Hindustani classical music, the tabla has achieved a distinctive position because of its tonal variety, rhythmic flexibility, and extensive use in both solo and accompanying roles. The artistic language of the instrument is expressed through bols, which function as the primary units of rhythmic articulation and are produced through specific techniques on the dayan and bayan. This paper explores the principal tabla bols and examines their methods of execution, acoustic characteristics, and significance in performance practice. Special emphasis is placed on the relationship between tabla and pakhawaj, two percussion traditions that share important technical and historical connections. By comparing corresponding strokes, hand movements, and sound-producing mechanisms, the study demonstrates how several elements of tabla technique developed from earlier pakhawaj practices while gradually adapting to the structural design of the instrument. The discussion further highlights the role of fundamental bols in shaping rhythmic expression, tonal clarity, and stylistic identity. The findings suggest that the evolution of tabla represents a process of continuity and innovation in which inherited percussion techniques were transformed into an independent and sophisticated performance system. Such an understanding contributes to the broader study of Indian percussion traditions and their historical development.

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Tabla, Pakhawaj, Bol System, Indian Percussion Instrument, Hindustani Classical Music, Rhythm, Tala

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Circular Reasoning in Geometrical Proofs: A Critical Discussion

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ABSTRACT Plant pest and disease management, especially in the early stages of infestation, is a critical challenge that poses significant threats and has potential to devastate agricultural crops, causing total yield loss and food insecurity. Traditional inspection methods are time-consuming and prone to errors due to limited labor expertise. Therefore, to tackle these challenges, harnessing advanced technologies such as artificial intelligence (AI), Machine Learning/Deep Learning (ML/DL), and Internet of Things (IoT) is essential for managing and mitigating agriculture hazards. This article presents a comprehensive review of the state-of-the-art DL architectures integrated with IoT-based systems applied to plant pest and disease detection (PPDD) by investigating different potential approaches that have been employed using DL and IoT up to the year 2024 to address challenges in agriculture. Convolutional Neural Network (CNN) architectures for image recognition, object detection, and their integration with IoT, embedded into mobile devices and unmanned aerial vehicles (UAV) are explored. Moreover, the research discusses the advantages and limitations of these techniques, emphasizing their architecture design, efficiency and accuracy. The findings demonstrate that there is a tradeoff between robustness and complexity among existing techniques, and authors recommend future trends aimed at creating robust models with fewer parameters that are more accurate and easily implementable on small IoT-based and portable devices suitable for in-field and real time applications. Furthermore, while existing review papers discuss either DL or IoT separately, this research paper uniquely focuses on their combined models, providing a comprehensive overview of the synergistic potential of leveraging IoT-driven technologies alongside advanced DL algorithms to ease the task of researchers in the field of precision agriculture particularly in PPDD.

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DL,PPDD,UAV, CNN, IOT

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Modern society has become increasingly fast-paced, technologically driven, and productivity-oriented, contributing to the emergence of autopilot living.This literature review examines the psychological concept of autopilot mode by exploring its theoretical foundations, contributing factors, psychological consequences, and intervention strategies. A qualitative narrative literature review methodology was employed, involving the analysis of academic books, peer-reviewed journal articles, and psychological studies related to automaticity, mindfulness, habit formation, burnout, digital behavior, and emotional regulation.The review findings indicate that although automatic cognitive processing is a normal and necessary aspect of human functioning, excessive reliance on habitual and unconscious behavior may reduce reflective awareness, emotional responsiveness, and intentional decision-making. Factors such as repetitive routines, digital overstimulation, occupational stress, emotional avoidance, and productivity-centered lifestyles were identified as major contributors to unconscious living patterns. The literature further revealed several psychological consequences associated with autopilot functioning, including emotional numbness, anxiety, depression, burnout, reduced life satisfaction, identity disconnection, and relationship difficulties.The review also highlights the effectiveness of intervention strategies such as mindfulness meditation, behavioral novelty, digital detoxification, physical exercise, and psychotherapy in promoting conscious awareness, emotional regulation, and psychological flexibility. The findings suggest that autopilot living is both a psychological and societal phenomenon shaped by modern environmental conditions. While automaticity supports efficient daily functioning, excessive dependence on unconscious behavioral patterns may negatively affect psychological well-being and meaningful life engagement. Therefore, promoting mindfulness, reflective awareness, and intentional living appears essential for maintaining psychological health in contemporary society.

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Autopilot living, automaticity, mindfulness, habit formation, digital overstimulation, emotional regulation, burnout, psychological well-being.

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Creative Commons Attribution 4.0 and The Open Definition

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Knowledge is the Supreme Power of society. The ancient times, knowledge has been acquired through various Process of learning such as Shravana(listening),Manana (contemplation), and Nididhyasana (deep meditation).Education and knowledge both are interrelated. The modern education policy currently formulated is the National Education Policy (NEP) 2020.The Indian knowledge system acquisition outlined in this education policy has assumed a significant role in modern society. Indian Knowledge System (IKS) enables a holistic approach.IKS focuses on sustainable development in the society and individuals. Through this article, we will examine the concepts, opportunities and challenges associated with the Indian Knowledge Systems as outlined in the National Education Policy. Furthermore, we will explore potential strategies to address these existing issues. Additionally, an endeavor has been made to demonstrate how, within the context of modern society, the scope of its application can be expanded to ensure that people from all individuals of society benefit from this knowledge The study adopts a descriptive Research based on secondary data including policy Papers s, academic literature reviews, and government reports. were carefully analyzed to understand the conceptual framework of the Indian Knowledge System.

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 Keywords

Nep 2020, Indian Knowledge System, Concepts ,opportunities, challenges, holistic development.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition