Volume 13 | Issue 4 |

 Abstract

Surface plasmon resonance (SPR) sensors offer a powerful tool for label-free and real-time monitoring of biomolecular interactions and to detect very low concentrations of chemical substances. Sensitivity of these sensors can be enhanced using thin metal films for the generation of surface plasmons. Based on the thickness and quality of the metal films, minute changes in the refractive index corresponding to biochemical events can be detected. Current study focuses on the biochemical sensitivity of glucose molecules on the thin film based SPR sensors. Copper was taken as the base metallic material for the preparation of thin film for generation of surface plasmons. The nature of SPR response of this metallic film was analysed by wavelength scanning method and for various thickness. Then its sensitivity to glucose molecule was studied by simulating a glucose solution environment above the metallic film. The SPR response was recorded for change in the refractive index of the order of 0.001. By optimizing the thickness and wavelength of excitation radiation, a very high sensitivity to glucose was obtained for copper thin film based SPR sensors.

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 Keywords

Sensitivity, Surface plasmon resonance, copper thin film, biochemical sensor

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 Abstract

Biomedical imaging is pivotal in diagnostics, treatment planning, and medical research. However, the quality of biomedical images is often compromised due to various sources of noise during acquisition. This paper proposes an AI-driven denoising framework aimed at enhancing biomedical image quality. Leveraging deep learning techniques, particularly convolutional neural networks (CNNs), the proposed method effectively suppresses noise while preserving structural details crucial for clinical interpretation. Experimental results demonstrate significant improvements in image quality metrics such as PSNR and SSIM, highlighting the framework's potential for integration into clinical workflows.

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 Keywords

Biomedical Image Denoising, Deep Learning, CNN, PSNR, SSIM, Medical Imaging, Flask Web App, RealESRGAN, Noise Classification.

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This paper explores the legal framework, applications, and challenges associated with electronic signatures (e-signatures) in India. It examines the provisions of the Information Technology Act, 2000, which grants legal recognition to e-signatures and discusses the role of Certifying Authorities in ensuring their security and authenticity. The paper highlights the different types of e-signatures, including simple electronic signatures (SES), digital signatures, and advanced electronic signatures (AES), and their use across various sectors such as government, finance, and healthcare. Additionally, the study compares India's e-signature laws with those of international jurisdictions like the United States and the European Union. The paper concludes with recommendations for improving infrastructure, streamlining regulations, expanding legal recognition, and promoting public awareness to enhance the adoption of e-signatures in India. With the growth of digital transactions, e-signatures are poised to become a crucial tool in the country's digital transformation.

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 Keywords

Electronic Signatures, Information Technology Act, Certifying Authorities, Digital Signatures, Legal

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Creative Commons Attribution 4.0 and The Open Definition

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Medicinal plants and their secondary metabolites are increasingly used as complementary medicines for the treatment of various diseases. Many synthetic anti-inflammatory drugs are associated with significant side effects and toxicity. In contrast, plant-derived anti-inflammatory agents have been traditionally used to manage inflammation with minimal adverse effects. Inflammation is a biological response in which the body's white blood cells and their mediators protect against infections caused by external pathogens such as bacteria and viruses. This review highlights various medicinal plants, their active constituents, and their role in combating inflammation. Additionally, it discusses previous research studies supporting their anti-inflammatory potential. The review concludes that herbal remedies are natural, safe, eco-friendly, and generally free from side effects. As modern lifestyles become increasingly detached from nature and technology-driven, there is a pressing need to promote the use of herbal medicine for better health and well-being.

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 Keywords

Anti-inflammatory agents, Inflammation, Medicinal plants, Secondary metabolites, Herbal medicine, Synthetic drugs.

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 Abstract

Samajik Parivartan Ke Liye Siksha Me Naitik Mulyo Ka Samavesh

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Samajik Parivartan Ke Liye Siksha Me Naitik Mulyo Ka Samavesh

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 Abstract

The concept of a supreme creator or almighty being in tribal societies, particularly among the Adivasis of India, differs significantly from the monotheistic or organized religious structures seen in Brahmanism, Christianity and Islam. Adivasi spiritual traditions are deeply rooted in animism, nature worship and ancestral reverence, emphasizing a decentralized belief system that does not conform to the notion of a singular "Parmeshwar" or universal god. Instead, these indigenous communities recognize and venerate local deities, spirits and sacred natural elements such as the sun, moon, rivers, forests, and mountains. Adivasi religious traditions are diverse and vary across different tribal groups. The Santhal tribe worships Thakur Jiu, while the Munda tribe believes in Sing Bonga and the Gond tribe venerates Bara Deo. These deities are often associated with natural forces and ancestral spirits, reflecting a holistic worldview where the environment is considered sacred. Rituals, festivals, and ceremonies such as Sarhul, Karam and Sohrai play a crucial role in maintaining the spiritual and ecological balance within Adivasi societies. Shamans, known as Pahans, Dehuris and Ojhas, act as intermediaries between the human and spiritual realms, conducting rituals to appease spirits and ensure community well-being. Adivasi spiritual traditions contrast sharply with organized religions, as they lack a formal priesthood, religious scriptures, and centralized religious institutions. However, due to colonial influences, religious conversions, urbanization and government policies, many Adivasis have been compelled to adopt mainstream religious practices, often at the cost of their indigenous faiths. The Sarna Dharma Recognition Movement is an ongoing effort to obtain legal recognition for tribal religious practices, ensuring their preservation and protection. Despite challenges posed by industrialization, deforestation and migration, tribal communities continue to resist cultural assimilation and reclaim their spiritual heritage through grassroots movements and legal activism. Efforts to document and revive indigenous oral traditions, protect sacred groves and promote cultural awareness have gained momentum in recent years. Recognizing and respecting Adivasi spirituality is crucial not only for cultural preservation but also for ecological sustainability and social justice. This study explores the unique aspects of Adivasi religious traditions, the impact of external forces and the ongoing struggle for recognition and revival of indigenous belief systems in India.

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 Keywords

Adivasi Spirituality, Animism, Nature Worship, Tribal Deities, Sarna Dharma, Indigenous Religions, Ancestral Worship, Sacred Groves, Rituals and Festivals, Religious Conversions, Legal Recognition, Cultural Preservation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

E-commerce businesses increasingly rely on AI to enhance customer interactions and provide real-time support. This project focuses on developing a Live Chat-Bot that enables seamless communication between customers and an e-commerce clothing website. Utilizing Natural Language Processing (NLP) and AI, the chatbot is designed to provide instant assistance, personalized recommendations, and 24/7 customer support, reducing the need for human intervention while improving the shopping experience. It integrates with the website's backend to analyze user preferences and guide them toward relevant products, ensuring an interactive and efficient shopping process. The chatbot offers key advantages such as instant query resolution, increased conversion rates, and enhanced user engagement. Built with Flask and Django, and leveraging cloud-based infrastructure, it can handle multiple inquiries simultaneously. However, challenges such as data privacy concerns and miscommunication risks must be addressed. Overall, the implementation of this chatbot aims to revolutionize e-commerce customer support, making it more efficient, scalable, and user-friendly.

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 Keywords

E-commerce,Chatbot,AI,NLP,Real-time support,Customer engagement Personalized recommendations,Flask,Query resolution,Scalability.

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Creative Commons Attribution 4.0 and The Open Definition

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Studies of gender and its relations to resources, cultural and environmental milieu has been an important theme in the social and cultural Geography. Bodos have patriarchal society which guide social norms and cultural conditions that have resulted into a distinct subordination of relationship on the basis of gender among the Bodos. This is reflected in the heritance of property between the male and female members in the family or in the community. Heritance of property by Bodo women is confined within tangible material goods like handloom items, share in agricultural products, dresses, gold-silver ornaments, domestic animals, etc. Bodo women are deprived of attaining the intangible and valuable properties like quality higher education, land ownership, right and freedom to economic activities, right and liberty for political standouts. Such practices of the society is an outcome of patriarchy and acceptance of women as paraya dhan i.e. (else's property) leading to gender disparity and poverty in the community as a whole. Overall sustainable development can only prevail in a community if the women are privileged to equally participate in the dynamics of property inheritance.

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 Keywords

Gender, Property, Rights, Bodo, Community.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTACRT: forest algorithm and the Adaboost algorithm. The results of the two algorithms are based on accuracy, precision, recall, and F1-score. The ROC curve is plotted based on the confusion matrix. The Random Forest and the Adaboost algorithms are compared and the algorithm that has the greatest accuracy, precision, recall, and F1-score is considered as the best algorithm that is used to detect the fraud. UPI fraud detection is presently the most frequently occurring problem in the present world. This is due to the rise in both online transactions and e-commerce platforms. UPIfraud generally happens when the card was stolen for any of the unauthorized purposes or even when the fraudster uses the UPI information for his use. In the present world, we are facing a lot of UPI problems. To detect the fraudulent activities the UPIfraud detection system was introduced. This project aims to focus mainly on machine learning algorithms. The algorithms used are random.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords UPI, Fraud Detection, Machine Learning, Anomaly Detection, Financial Security, Real-time Analysis

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's data-driven retail environment, accurately forecasting profits and understanding customer behavior are vital for strategic decision-making. This project presents an integrated AI-powered framework for profit prediction and behavioral clustering in retail, leveraging the capabilities of deep learning models. A neural network-based regression model is developed to predict retail profit using historical sales, customer, and product data. To enhance the interpretability of the model, SHAP (SHapley Additive exPlanations) values are used to explain feature contributions, enabling actionable business insights. For customer segmentation, the project utilizes autoencoders to extract latent features from high-dimensional behavioral data, followed by clustering techniques to identify distinct customer profiles. This dual approach not only improves forecasting accuracy but also aids in personalized marketing and inventory optimization. The system is deployed using Streamlit, offering an interactive and user-friendly interface for stakeholders. The proposed solution demonstrates the potential of deep learning in transforming retail analytics through predictive modeling and intelligent customer segmentation.

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 Keywords

Retail Analytics, Profit Prediction, Neural Networks, Customer Segmentation, Autoencoders, Deep Learning, Behavioral Clustering, SHAP Explainability, Predictive Modeling, Streamlit Deployment, Data-Driven Decision Making, Machine Learning, Feature Importance, Sales Forecasting, Unsupervised Learning.

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