Volume 13 | Issue 4 |

 Abstract

This paper examines Anita Desai's Cry, the Peacock (1963) as a powerful critique of gendered oppression and the silencing of women's voices within the patriarchal context of 1960s India. Through an in-depth analysis of the protagonist Maya's psychological deterioration, the study explores how Desai portrays the impact of marital alienation, societal expectations, and emotional invalidation on women's mental health. The paper argues that Maya's internal turmoil--symbolized through literary motifs such as the peacock's cry, dust storms, and moon imagery--serves as a silent rebellion against systemic marginalization. Drawing from feminist literary theory and postcolonial perspectives, the analysis underscores how Anita Desai uses narrative techniques and symbolism to reveal the devastating effects of silenced emotional needs and gendered subjugation. The findings illuminate the novel's enduring relevance to feminist discourse, particularly in its exploration of psychological trauma, female agency, and resistance within oppressive social structures.

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 Keywords

gendered oppression, silenced voices, female marginalization, patriarchy, psychological realism, feminist literature, symbolism

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract The Telangana government's initiative to construct Young India Integrated Residential Schools (YIIRS) marks a significant shift in the state's education policy, aiming to replace Caste-segregated residential schools with a unified, inclusive model. With an allocation of INR11,000 crore for 55 schools (INR200 crore each), the project promises international standard education while fostering social harmony . However, challenges such as land Acquisition delays, funding constraints, and equity concerns raise questions about its Feasibility. This study examines the objectives, implementation strategies, and potential impact Of YIIRS, analysing its merits, demerits, and long-term viability.

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Keywords : Holistic education , Inclusivity, Quality Education, social integration, Transformative Education, world class education, Uniform Distribution, Equity and Equality.

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Water body segmentation using satellite imagery is essential for flood monitoring, environmental planning, and sustainable resource management. This study proposes a deep learning-based framework for semantic segmentation using SegFormer and DeepLabV3+ models, trained on a combination of Sentinel-1 (SAR) and Sentinel-2 (optical) satellite data. The pipeline includes preprocessing using Google Earth Engine (GEE), cloud storage and access via AWS S3, and training on AWS EC2 GPU instances. Evaluation metrics such as IoU, F1-score, Precision, and Recall confirm the superiority of our model over traditional threshold-based methods. The system supports scalable, real-time monitoring for diverse geographic regions and climatic conditions.

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Water body segmentation using satellite imagery is essential for flood monitoring

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The above literature drives home the fact that many studies done on Hassan district have touched upon various aspects and they are diverse in nature.

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Abstract Personal data is an asset or a product of high economic value. Furthermore, there is a correlation between the level of trust and the protection of specific data from personal life. In India, crimi-nals have developed as a major concern for businesses with rapidly expanding business sectors and increasing numbers of corporate fraud cases. This report provides a comprehensive analysis of criminal liability for Indian companies. In the Modern era, corporate crime has become a big-ger problem for the judiciary system as a whole. Personal data protection is not currently regu-lated by other laws, but continues to be distributed among a variety of laws and regulations. Le-gal provisions relating to the protection of personal data remain sector based. It appears that in the context of privacy, optimal and effective protection could not be provided. If you see a victim of a corporate crime for the criminal act of escaping personal data, it is very natural that the company must be responsible for all of its actions. The guilt of crime comes from the saying. Legal proverb: "Actuated Non-Fast Rium Nishi men's sitting means that their actions will not be considered illegal if they are committed in an illegal state of mind. This is the basis of criminal responsibility. These are business related crimes committed by organizations. India can learn from other countries to improve its legal system and increase the responsibility of businesses to protect its financial system. Bad regulations and gaps in India have led to famous incidents and econom-ic mistakes. The types of losses and impact of corporate crimes are felt later (of actual victims) and seen later (by potential victims). Competitive businesses, customers, and the general public are among the victims of corporate crime. This research paper examines data abuse and gaps and challenges, controversy, law, and criminal liability for data for Indian judgments.

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criminal liability,CorporateCriminalLiability,data protection

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Creative Commons Attribution 4.0 and The Open Definition

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In the study of physical quantities, the structure faces the problem of crack's presence. We use Integral equation to solve such problems. In this paper we deal with two exterior Griffth cracks which are opened by force at crack surface. Here we get the integral equations which are reduced to Fredholm integral Equations, It is easy to make exterior Griffth crack to perform the experiment. Hence the problem is of physical importance and special case of loading is discussed.

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Griffth crack, Fredholm Integral equation

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents the design and development of a web-based backtesting platform tailored to the needs of retail traders exploring algorithmic trading. The platform provides an intuitive interface for uploading or fetching historical financial data, configuring machine learning models, and simulating trading strategies with customizable parameters such as commission, slippage, and initial capital. Built using modern web technologies including React, TypeScript, and Tailwind CSS, the system integrates backend services for model training and trade simulation. It supports realistic backtesting by incorporating data preprocessing, strategy validation, and performance visualization. The platform aims to make algorithmic trading more accessible by simplifying complex workflows and promoting transparency in model evaluation. Results demonstrate the platform's responsiveness and usability, highlighting its potential for educational use and individual strategy exploration. Future work includes extending support for additional models, real-time execution, and portfolio management features to further enhance its functionality.

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algorithmic trading, backtesting platform, machine learning, web-based simulation, financial technology

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Creative Commons Attribution 4.0 and The Open Definition

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In the era of digital innovation, crowdfunding has emerged as a vital mechanism for financing projects, especially those driven by startups and individuals. However, traditional crowdfunding systems often face challenges related to fraud, lack of transparency, and delays in fund allocation. This paper proposes a blockchain-based crowdfunding system that leverages Ethereum smart contracts, decentralized storage (IPFS), and web technologies (ReactJS and NodeJS) to mitigate these issues. By employing smart contracts, the system ensures that funds are released only when predefined conditions are met, thus fostering trust and transparency among contributors. The system's architecture is designed for decentralized interactions, allowing contributors to track campaign progress, vote on expense approvals, and securely access stored documents. Our approach highlights the immense potential of blockchain in transforming crowdfunding by improving security, efficiency, and accountability.

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Creative Commons Attribution 4.0 and The Open Definition

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Blockchain, Smart Contracts, Crowdfunding, Ethereum, IPFS, ReactJS, Decentralized Applications, Transparency, Data Security

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Creative Commons Attribution 4.0 and The Open Definition

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This paper aims at presenting a new model to ease group travel by integrating the traveler and travel agency. The model works by uniting people with matching travel goals so that they can form groups effortlessly. Therefore, travel agencies can now provide specific groups with customized rental cars and travel packages. The above system tackles issues faced in conventional travel booking and increases user satisfaction while also enabling agencies to profit from it. This review details problem definition, exploration, goals, architectural design, methods used, conclusions drawn, pros, cons, and possible future of the platform.

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Group travel ,Traveler , Travel Agency , Model , Customize rental cars , travel packages , User satisfaction, Conventional travel booking , Profit , System, Flutter, App development, Community, IOS app, Android app.

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Deep learning, with its automatic learning and feature extraction, has become a key tool in agricultural plant protection, particularly for disease and pest detection. This review explores recent advancements in deep learning for crop leaf disease identification, focusing on current trends and the integration of advanced imaging techniques. We examine the benefits over manual feature selection, discuss the challenges, and aim to provide a valuable resource for researchers in plant disease and pest analysis.

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Creative Commons Attribution 4.0 and The Open Definition

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plant disease; deep learning; convolutional neural networks (CNN).

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Creative Commons Attribution 4.0 and The Open Definition