Volume 13 | Issue 6 |

 Abstract

Indian cinema has always been more than just a form of entertainment; it's the heartbeat of our collective story, telling us who we are and who we aspire to be. In the early days before independence, filmmakers quietly but powerfully wove anti-colonial messages into their stories, quietly kindling cultural pride and unity. After 1947, the silver screen became a mirror to our nation's hopes and hardships, boldly addressing the struggles of poverty, social injustice, and the fragile dreams of freedom. The 1970s and 1980s marked a turning point: heroes with a fire in their hearts, the iconic "angry young men", stood up against corruption and inequality, giving voice to the frustrations of everyday people. Fast-forward to the present, and Indian films have embraced globalisation without losing their soul. Movies like Lagaan and Uri: The Surgical Strike captivate us not only with epic storytelling but also with themes of resilience, self-reliance, and patriotic pride. Through a thoughtful mix of content analysis, literature insights, and historical perspective, this study dives into the symbols, narrative techniques, and cinematic moments that have continuously inspired a shared sense of national identity.

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 Keywords

nationalism, cultural identity, cinematic symbolism, public sentiment, patriotic cinema, social justice

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid and accurate detection of COVID-19 has been crucial in mitigating the spread of the virus and ensuring timely medical intervention. This study presents a deep learning-based approach utilizing neural networks for the early detection of COVID-19 from clinical and radiological data. By leveraging convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the proposed model achieves high sensitivity and specificity in distinguishing COVID-19 cases from other respiratory conditions. The framework incorporates data preprocessing, feature extraction, and model optimization techniques to enhance diagnostic performance. Experimental results demonstrate the model's effectiveness in providing rapid, reliable screening, offering a promising tool for frontline healthcare systems, especially in resource-constrained environments. This research highlights the potential of deep learning as a transformative solution in pandemic response strategies, emphasizing the importance of AI-driven healthcare innovations.

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 Keywords

COVID-19 Detection, Neural Networks, Deep Learning, Rapid Screening, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Medical Imaging, Artificial Intelligence in Healthcare

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Sugarcane (Saccharum officinarum) is a vital commercial crop that significantly impacts the global economy, particularly in sugar and ethanol production. Proper management of sugarcane cultivation and its byproducts is crucial to enhancing productivity, reducing waste, and promoting sustainability. This review examines key aspects of sugarcane management, including optimal cultivation techniques, pest and nutrient control strategies, and harvesting methods. Additionally, it explores the effective utilization of byproducts such as bagasse, molasses, and press mud in biofertilizer production, energy generation, and other industrial applications. Furthermore, the study highlights emerging technologies and sustainable waste management strategies within the sugarcane industry. By implementing efficient farming and processing techniques, it is possible to increase yield while minimizing environmental impact, ensuring the long-term sustainability of the sugarcane sector.

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MANAGEMENT OF SUGARCANE AND ITS BY PRODUCTS

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Soil fertility constitutes a key factor in influencing the precise prediction of soil fertility classes, as well as agricultural productivity is important to optimizing agriculture practices. Classical soil fertility assessment methods are often labor intensive and costly. Machine learning based approaches are therefore an attractive alternative for improving efficiency. In this research, a novel method is introduced as a stacking ensemble method for soil fertility classification, which combines models. Each individual model is trained separately and their forecasts are combined through a meta-model in order to improve categorization ability.Unlike traditional single-model approaches the ensemble method effectiveness compared to individual models is assessed using classification metrics like F-1 measure, accuracy, sensitivity.The ensemble outperforms the the individual models demonstrating improved robustness and predictive reliability over existing techniques highlighting its potential for providing more robust and reliable soil fertility predictions.compared to previous approach this method provides more stable performance across fluctuations in nutrient levels and PH.This approach shows promising applications in precision agriculture, offering improved decision-making for soil management. Future studies aimed at improving performance could integrate data input such as sensor data.

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 Keywords

Decision Tree,Gaussian NB,KNN,Logistic Regression,Machine Learning,stacking ensemble

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Creative Commons Attribution 4.0 and The Open Definition

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The widespread availability of nucleotide and amino acid sequence data has enabled the development of advanced methods for identifying biologically and clinically significant information. Online platforms such as GeneCards offer accessible repositories for extended research and academic exploration. Additional protein-related data can be retrieved from databases like UniProt and SwissProt. Tools such as FASTA and Clustal_X are commonly used to calculate sequence similarity, aiding in the selection of target genes. In addition, text mining serves as a valuable technique for extracting relevant knowledge from scientific literature.

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FASTA, Clustal_X, Genomic Data, Genetic Sequences, Bioinformatics

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Creative Commons Attribution 4.0 and The Open Definition

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This paper uses machine learning models to detect lung cancer early using patient data. Random Forest showed the best accuracy, offering a low-cost and effective diagnostic tool for early detection.

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 Keywords

Lung Cancer, Early Detection, Machine Learning, Patient Records, Clinical Symptoms, Predictive Modelling, Medical Diagnosis, Structured Data, Support Vector Machine (SVM), Random Forest, Logistic Regression, Cancer Risk Prediction, Artificial Intelligence in Healthcare, Health Informatics, Non-Invasive Diagnosis

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Rabindranath Tagore, Nobel laureate, poet, philosopher, and educationist, holds a unique place in the history of modern education in India. His educational philosophy, rooted deeply in Indian tradition yet strikingly modern and progressive, presents a holistic vision of human development. This research paper explores Tagore's views on education, analyzing their philosophical foundations, practical applications, and continued relevance in contemporary educational discourse. At the core of Tagore's educational thought lies the idea of freedom--freedom of expression, thought, and the natural development of the child. He believed that education should not be a mechanical transmission of information but a living, dynamic process that nurtures creativity, critical thinking, and emotional growth. Tagore's educational philosophy was heavily influenced by his personal experiences with formal schooling, which he found rigid, uninspiring, and disconnected from nature and creativity. As a response, he developed an alternative model at Visva-Bharati, the institution he founded at Santiniketan in 1921. Here, education was designed to harmonize the mind, body, and soul through a curriculum that emphasized arts, music, literature, nature, and cultural exchange. Tagore emphasized learning through activity, the importance of aesthetic development, and the need for education to foster global understanding and unity. His critique of rote learning and authoritarian instruction systems positioned him as a pioneering voice for child-centered and experiential learning. The paper delves into the spiritual and philosophical underpinnings of Tagore's thoughts, drawing from Upanishadic teachings, Romanticism, and humanism. He envisioned education as a means of realizing the inner self and establishing a deep, harmonious relationship with the universe. According to Tagore, the aim of education is not merely to impart knowledge or vocational skills but to cultivate an individual's moral, intellectual, and spiritual potential. His belief in the inherent divinity of the child led him to advocate for an educational environment that respects individuality and fosters joy, curiosity, and compassion.

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Rabindranath Tagore on Nature Education

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Creative Commons Attribution 4.0 and The Open Definition

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"Indian Constitution" provides certain safeguards to "Scheduled Tribes" as detailed in "Schedules V and VI". "705 Scheduled Tribe" people are acknowledged under "Article 342 of the Constitution of India". "Scheduled Tribes" constitute "8.6 percent" of "India's total population (Census of India, 2011)", inhabiting around "15 percent" of the geographical area across varied ecological and geo-climatic conditions, primarily in forested, mountainous, and border regions" In India "75 Tribal groups" across "18 states and union territories", including the "Andaman and Nicobar Islands", have been identified and classified as "Particularly Vulnerable Tribal Groups (PVTGs)" due to their "declining or stagnant populations, low literacy rates, pre-agricultural technology, and economic disadvantage". The advancement of the "Tribal community" has captured the "government's focus" since "independence". Efforts for the "welfare and development of Tribal communities" have progressed from the creation of "Scheduled Tribes" via "Community Development Programmes and Special Multipurpose Tribal Development Blocks" to the execution of the "Tribal Sub Plan". This "book chapter" elucidates the empowerment of "Tribal populations" through "transformational reforms and various welfare programs" undertaken by the "government" within the "Indian context".

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"Constitution, Community Development, Geographical, Initiative and Welfare - reg."

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Creative Commons Attribution 4.0 and The Open Definition

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This paper explores the evolving relationship between Artificial Intelligence (AI) and education, highlighting future trends, potential transformations, and the critical challenges ahead. The study investigates how AI-driven personalization, adaptive learning technologies, automated assessment, and intelligent tutoring systems are reshaping educational experiences. Simultaneously, it addresses ethical concerns, digital divide issues, and the implications of AI on the role of teachers and educational equity. The paper draws from interdisciplinary research and proposes a balanced framework for sustainable AI integration in global education systems.

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 Keywords

Artificial Intelligence, Education Technology, Personalized Learning, Intelligent Tutoring Systems, AI in Classrooms, Automated Assessment, Learning Analytics, Educational Equity, Digital Ethics, Future of Education.

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Creative Commons Attribution 4.0 and The Open Definition

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A Mental Health Information System (MHIS) is designed to systematically collect and analyze data on mental health services and population needs, aiming to enhance care effectiveness and ensure equitable service delivery. It provides timely information to support informed decision-making for improving care quality.This study examines health information use within Kerala's progressive mental health care system, utilizing records, surveys, and interviews to understand utilization among caregivers and decision- makers.Data were organized in Microsoft Excel and analyzed with SPSS version 23, using descriptive statistics, Chi-square tests, and Fisher’s exact tests to explore relationships between categorical variables. Data visualization, such as histograms, highlighted key trends and patterns.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Health information, Management, Mental Health, Mental Health Care Establishments.

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Creative Commons Attribution 4.0 and The Open Definition