Volume 14 | Issue 6 |

 Abstract

Religious tourism is an important and continuous segment of travel in Andhra Pradesh because it links faith, culture, local mobility, community livelihoods and public infrastructure. This study examines the socio-economic contribution of religious tourism in Andhra Pradesh with special focus on Tirumala Tirupati Devasthanam, Srisailam Temple and Vijayawada Kanaka Durga Temple. A descriptive and analytical research design was adopted by using both primary and secondary data. Primary data were collected through a structured questionnaire from 174 respondents, including pilgrims, local residents and service providers. Secondary information was compiled from the Ministry of Tourism, Government of India, official temple websites, tourism statistics and relevant published sources. Percentage analysis, weighted mean score, expenditure estimation, district-wise tourist visit comparison and a one-sample proportion z-test were used for interpretation. The findings show that religious tourism contributes to employment generation, local business activity, accommodation services, transport, prasadam and food services, shopping, cultural practices and infrastructure development. The primary survey indicates that 66.09 per cent of respondents agreed or strongly agreed that religious tourism creates employment and income opportunities for local people. At the same time, crowding, waiting time, accommodation shortage, high prices and language-related difficulties remain major concerns. The study concludes that religious tourism can become a stronger tool of inclusive and sustainable development when temple administration, local bodies and tourism departments coordinate sanitation, digital services, skill development, crowd management and responsible destination planning.

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 Keywords

Religious Tourism; Pilgrimage Tourism; Socio-Economic Development; Andhra Pradesh; Tirumala Tirupati Devasthanam; Srisailam Temple; Kanaka Durga Temple.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Artificial Intelligence (AI) has emerged as a transformative force in contemporary organizations, fundamentally reshaping business processes, workforce practices, and operational strategies. The increasing integration of AI technologies, including machine learning, intelligent automation, predictive analytics, and data-driven decision-support systems, has significantly influenced how organizations manage resources, improve productivity, and achieve competitive advantage. Within India's rapidly expanding information technology sector, Pune has evolved as a major technology hub where organizations are actively investing in AI-driven solutions to enhance performance and operational effectiveness. The present study seeks to examine the impact of AI adoption on employee performance and organisational efficiency in the IT industries of Pune. While existing literature highlights the strategic benefits of AI, there remains limited empirical evidence regarding its measurable influence on workforce productivity and organizational outcomes within specific regional contexts. This research addresses this gap by investigating the extent to which AI adoption contributes to employee productivity, task efficiency, work quality, decision-making capability, and overall organizational effectiveness. The study adopts a mixed-methods research design that integrates quantitative and qualitative approaches. Quantitative data will be collected through structured questionnaires administered to employees and managers across selected IT organizations in Pune. Qualitative insights will be obtained through semi-structured interviews with industry professionals and organizational leaders. An AI Adoption Index will be developed to assess the degree of AI implementation based on factors such as automation intensity, AI tool integration, and organizational investment in AI technologies. Employee performance will be evaluated through indicators including productivity rate and task completion efficiency, while organizational efficiency will be measured using operational parameters such as process turnaround time, cost optimization, and resource utilization. Advanced statistical techniques, including correlation, regression, and mediation analysis, will be employed to examine the relationships among AI adoption, employee performance, and organizational efficiency. The study will also explore whether employee performance serves as a mediating factor between AI implementation and organizational outcomes. Furthermore, qualitative findings will provide deeper insights into employee perceptions, challenges, opportunities, and organizational readiness associated with AI adoption. The anticipated findings are expected to contribute to both academic and managerial knowledge by offering empirical evidence on the effectiveness of AI in enhancing organizational performance. The research will provide valuable recommendations for IT organizations, policymakers, and human resource professionals regarding sustainable AI integration, workforce development, and strategic decision-making. By focusing on Pune's IT ecosystem, the study will generate region-specific insights that can support organizations in maximizing the benefits of AI while addressing challenges related to employee adaptation, skill development, and organizational transformation. Ultimately, the research aims to advance understanding of how AI can be leveraged to achieve improved employee performance and greater organizational efficiency in a rapidly evolving digital environment.

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 Keywords

Keywords: Artificial Intelligence, Employee Performance, Organisational Efficiency, IT Industry, Pune, AI Adoption, Productivity, Digital Transformation, Human Resource Management, Organizational Performance.

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 Abstract

Without Resources an organisation is incomplete. An organisation is composed of four resources namely men, material, money and machinery. These 4 resources play a very important role in every organisation. From these 4 resources one is living i.e human being and others are non living. Without human beings no organisation can achieve their target. The organisation cannot achieve their goal without human beings effort. Hence, human beings are most significant asset of every organisation. Human resources are nothing but all the people ranging from lower level management to upper level management. In every organisation there are talented, intelligent, motivated, hardworking, sincere workforces who represent brand value for every organisation. Therefore we can say that they are the real asset of an organisation. Health sector is one of the most challenging sectors of our country. The shortage of human resources in health sector may cause to death. The scarcity of qualified person in health sector is a very big problem in Orissa. In Orissa there is less no of qualified health workers in rural areas. There is more absenteeism of health workers especially in rural areas in Orissa.

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 Keywords

Human resources, Brand value, Asset, Workforce, Health care, Absenteeism

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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

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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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 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

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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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 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

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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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 Keywords

DL,PPDD,UAV, CNN, IOT

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Creative Commons Attribution 4.0 and The Open Definition