Volume 10 | Issue 7 | July-2022

 Abstract

Voting is a central component of a country's political life cycle. Privacy, authentication and integrity of citizens' votes and their data are considered to be essential to any e voting program. In order to resolve these concerns, we propose a stable e-voting system based on the principles of blockchain, machine learning and cryptography. We use block chain for immutable vote recording, machine learning model to detect intrusion in voting data centers and e-voting stations, and cryptography for secure voter authentication and data protection. The proposed a blockchain-based e-voting system designed exclusively for physically disabled citizens who are unable to visit polling stations. The system facilitates secure, transparent, and tamper-proof voting by allowing Election Commission (EC) officials to conduct supervised voting at the voter's home using a blockchain-integrated mobile voting device.The system ensures vote integrity, voter privacy, and auditability while addressing accessibility concerns for this marginalized demographic.

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Electronic -Voting System Using Machine Learning and Cryptography

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Indigenous knowledge, both at the national and international level, is increasingly being exploited and commercialised by non indigenous people. Despite high commercial value of traditional knowledge indigenous people often derive little or no benefit from the market consumption of their traditional knowledge. The main problem of enforcing rights for contemporary indigenous groups stems from the dichotomy between the values systems of western and indigenous culture. The values of indigenous culture do not fit within the western concept of the egocentric individual that is the current focus of the legal regime today. Current intellectual property rights such as copyright, patent and trademark laws for protection of traditional knowledge are either insufficient, ad-hoc, or uncertain. However, other difficulties for protection of traditional knowledge include desire for perpetual protection, which is not available given the limited terms of western intellectual property laws and notion of communal ownership of traditional knowledge which has not been accepted in the intellectual property law. This article discusses the role of sue-generis system for the protection of traditional.

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Traditional, Indigenous, Knowledge, Sui-generis, Protection, Exploitation, Intellectual Property.

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This study explores an eco-friendly approach to handmade paper production using banana fiber extracted from agricultural waste, specifically banana pseudostems. As a sustainable alternative to conventional wood-based paper, this method addresses key environmental concerns, including deforestation and solid waste accumulation.The process begins with the collection of banana pseudostems, which are sun-dried and thoroughly washed to eliminate dust and impurities. The cleaned fibres are then treated with a 10% caustic soda solution and cooked under pressure to break down the lignocellulosic structure, facilitating pulp formation. Once softened, the fibres are mechanically blended into a uniform pulp and cast into sheets for handmade paper production. To evaluate the quality of the resulting paper, several physicochemical parameters were analysed, including grammage (GSM), pH, thickness, bulk, and moisture content. Results indicate that the paper is lightweight, biodegradable, and free from synthetic additives or harsh chemicals. Its smooth texture and satisfactory mechanical strength render it suitable for lightweight paper applications such as tissue paper, wipes, and tracing paper. This environmentally responsible method reduces the reliance on chemical bleaching and promotes the efficient conversion of agricultural residues into value-added materials. The process is cost-effective, simple, and scalable, presenting opportunities for rural employment and micro-enterprise development. By transforming agrowaste into functional products, this initiative aligns with circular economy principles and supports sustainable development goals. The findings highlight the commercial potential of banana fibre-based handmade paper and its promising role in fostering a greener, more sustainable paper industry.

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Banana Fiber, Handmade Paper, Agricultural Waste, Lignocellulosic Fiber, Biodegradable Paper, Eco-friendly Process, Sustainable Paper Production

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Mahasweta Devi is a vital segment of India's indigenous literature. She is an activist cum writer who has carried a tireless crusade working, fighting and writing for the marginalized. Her writings render the excruciating dilemmas of humans at the social-periphery. Her works have been widely read and translated for their poignant themes and social commitment. Published in 1979, Old Women by Mahasweta Devi is a collection of two stories "Murti" (Statue) and "Mohanpurer Rupkatha" (The Fairy Tale of Mohanpur) that unveils the societal oppression encountered by the two women protagonists - Dulali and Andi. These stories were translated into English by Columbia University Professor Gayatri Chakravorty Spivak in 1999. Mahasweta Devi was honoured with the Ramon Magsaysay award in 1997. The present paper shall analyse Old Women in the light of the above given statement. The significance of these stories as an effective tool to define identity and existence of the otherwise deprived beings shall be enlisted. Mahasweta Devi's fine understanding of the marginalised psyche and her belief that those on the fringes cannot be heard till they speak shall be established. An attempt shall also be made to view that how the stories of the Old Women reveal the social matrix and construct a subaltern's perspective. The negative impact of exploitation and neglect that reduces people to a subhuman existence and the need to give voice to the voiceless shall be the major concern of this paper.

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 Keywords

marginalized, oppression, voice, subaltern, social commitment, crusade.

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The introduction of formal education by the British was strategically designed to support their administrative and bureaucratic needs rather than to uplift the native population. Opportunities for female education remained scarce. However, Christian missionaries played a somewhat progressive role in this context. Driven by religious motives, they established schools for girls, which often combined basic literacy with moral and religious instruction rooted in Christian values. Before colonial reforms, Indian women had minimal access to formal education. Despite the limited commitment of colonial authorities to women's empowerment, Indian social reformers emerged as powerful advocates for gender equality and educational access. This paper aims to discuss the colonial influence on women education, legal reforms, expansion of educational opportunity for women, impact of social reforms, challenge of women education and initiatives for the spread of women education in India.

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British Colonial era, Legal reforms, Social reformers, Educational opportunities, Challenges, Initiatives.

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Artificial intelligence (AI) is the ability of machines to carry out tasks by imitating human intelligence. In recent years, AI methods have begun to be applied in many different areas, with healthcare being one of the most prominent. Diagnosis, treatment, patient care, new drug production, and preventive care can be listed as some of the applications of AI in healthcare. In this review, deep learning and computer vision methods, which are a sub-branch of AI, are mentioned. Deep learning methods frequently used in the literature are convolutional neural networks (CNNs), stacked autoencoders (SAEs), and recurrent neural networks (RNNs). These deep learning methods include CNNs for image recognition and classification, SAEs for unsupervised feature learning and dimensionality reduction, and RNNs for analyzing sequential data like time-series. However, it should be noted that these methods can also be applied to other application areas. This paper presents studies in the literature on medical image analysis, drug discovery and development, and remote patient monitoring in which these deep learning methods are used.

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Artificial Intelligence (AI), Deep Learning (DL), Computer Vision (CV), Healthcare, Smart systems.

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Aluminium alloys are widely used in aerospace and automotive industries due to their advantages of physical and mechanical properties. This paper presents a study on the performance of stir cast SiC & Al2O3 reinforced Aluminium metal matrix composite materials. The particulate reinforcement of SiC & Al2O3 is in the ration of 3:2. The mechanical characterization of AMMC indicates that the composite exhibit improved physical and mechanical properties such as low coefficient of thermal expansion, high ultimate tensile strength, high impact strength and hardness. Through scanning electron microscope, the microstructure of AMMC & distribution of SiC & Al2O3 particles in Aluminium alloy (Al 1350) is uniform. By experimental analysis, it is observed that AMMC with 15% of particulate reinforcement of SiC & Al2O3 with a ratio of 3:2 (9% of SiC & 6% of Al2O3) is the optimum mixture for AMMC to obtain better mechanical characteristics. This AMMC has good potential for the applications in automotive industry to manufacture engine components.

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Characterisation of Aluminium Metal Matrix Composites reinforced with SiC (Carborundum) & Al2O3 (Corundum)

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The study of human beings is one of the many fascinating studies within religion, philosophy and the physical sciences for hundred years. In general when we observe a person over a long period of time, what we find is a certain pattern in his or her behaviour, feelings and even thinking. This pattern is said to be one's personality. The personality constitutes not only what others think about one but also one's estimation of oneself. It not only refers to the behaviour but also to dispositions and the mental impressions behind the behaviour. In all, what makes a person distinct from another is his or her personality. Personality development is the emergence of the thought and behavioral patterns of a human being over time. It is these traits that make one's personality. How do these patterns evolve and what are the conditions of such an evolutions? Whether the traits which manifest in a person already exist in a potential form or does the external ambience contribute to the acquisition of such traits? These are some of fundamental factors to be considered while assessing what personality development is. It is a multidisciplinary subject involving several branches of knowledge including philosophy. Religions, psychology and the like.

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The Vedantic Idea of Personality Development

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This article delves into the significant contributions of the Manas Maozigendri Eco-Tourism Society (MMES) in the sustainable development and conservation of the Manas region in Assam, India. Established in December 2003, MMES has played a pivotal role in fostering community participation, promoting eco-tourism, and preserving the rich biodiversity of the Manas Biosphere Reserve. The paper outlines the historical context of conservation efforts in Manas, dating back to its designation as a reserve forest in 1907 and subsequent recognition as a UNESCO World Heritage Site, Tiger Reserve, and Biosphere Reserve. Highlighting MMESs efforts in community awareness, wildlife protection, and eco-tourism, the article underscores the societys impact on socio-economic and educational development in the region. MMESs achievements, including numerous awards and recognitions, reflect its commitment to conserving Manas natural heritage while fostering sustainable livelihoods through eco-tourism.

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Manas Maozigendri Eco-Tourism Society, Sustainable Development, Conservation Efforts, Community Awareness, Eco-Tourism Initiatives

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The dynamic landscape of television viewership is influenced by numerous factors, including demographic shifts, content preferences, and viewing habits. To navigate these complexities, media companies and advertisers increasingly turn to predictive modelling techniques powered by M.L. This study explores the application of ML in forecasting TV viewership trends, aiming to enhance understanding and anticipation of audience behaviour. M.L. models offer robust tools for analysing large datasets and uncovering various ML algorithms, including regression models, decision trees, and neural networks, to predict viewership trends based on historical data. A comprehensive dataset encompassing TV ratings, demographic information, and time-series data forms the foundation of the analysis. In addition to leveraging M.L. techniques, this study integrates survey data to enrich the predictive models. A well-designed survey was conducted to gather insights directly from viewers about their preferences, viewing habits, and factors influencing their choices. This survey data is used to supplement the historical viewership data, allowing for a more nuanced and accurate prediction of trends. The results demonstrate that ML models can effectively capture and forecast viewership patterns, providing actionable insights for TV networks and advertisers. Key findings reveal that certain M.L. algorithms outperform others in prediction accuracy, highlighting the importance of model selection and tuning. Moreover, the incorporation of survey data enhances model performance by adding qualitative context to the quantitative data. The study also identifies several challenges in applying ML to predictive modelling of TV viewership, including data quality issues, the need for extensive computational resources, and the difficulty of capturing rapidly changing viewer behaviours. Despite these challenges, the findings underscore the potential of ML to transform how viewership trends are anticipated and managed.

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 Keywords

1. M.L. 2. Predictive Modelling 3. TV Viewership Trends 4. Data Analysis 5. Regression Models 6. Decision Trees 7. Neural Networks 8. Historical Data 9. Survey Data 10. Viewership Patterns 11. Media Companies 12. Advertising Strategies 13. Model Accuracy 14. Data Quality 15. Audience Behaviour

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