Volume 13 | Issue 2 |

 Abstract

RejecTech is an innovative Android-based application developed using Java, XML, and Firebase, designed to provide advanced call filtering and rejection mechanisms for enhanced user convenience and security. This application tracks and monitors all incoming calls, identifying spam or repetitive calls with high accuracy. Calls flagged as spam or persistently recurring can be automatically blocked, ensuring a distraction-free user experience. The app empowers users to set a "lag to red" threshold, enabling dynamic control over the spam detection sensitivity. Users can also monitor their call logs in real time and manually unblock specific numbers if needed, ensuring flexibility in managing blocked calls. With Firebase integration, the app ensures seamless data management and efficient processing of call records. RejecTech's robust call-filtering capabilities make it a reliable tool for reducing spam and repetitive call disruptions, enhancing both productivity and peace of mind.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Firebase, Android App, Call Block, Call Filter

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

We are a privileged generation living in this era full of technological advancements. Gone are the days when almost every work was done manually and now we are living in a time where a lot of work is done by machines, software, and various automated processes. In this regard, Artificial Intelligence (AI) has a special place in all the advancements of today. Artificial Intelligence or AI is nothing but the science of computers and machines that develop intelligence like humans. In this technology, machines are able to perform some simple to complex tasks that humans need to perform on a regular basis. Since AI systems are used day in and day out in our daily lives, it would not be wrong to say that our lives have also been upgraded with the use of this technology. AI systems are efficient enough to reduce human efforts in various fields. To perform various activities in the industry, many of them are using Artificial Intelligence to create machine slaves that perform various activities on a regular basis. Artificial Intelligence applications help in completing the work faster and with accurate results. Error-free and efficient world is the main objective behind Artificial Intelligence. In recent years, many sectors have started using AI technology to reduce human efforts and get efficient and faster results. Obviously, the positive potential of Artificial Intelligence is indeed huge and still untapped. One of the major disadvantages of Artificial Intelligence is the potential theft of personal data, especially in healthcare, education and other sectors, as well as the misuse of citizen databases by private companies and security agencies. Artificial Intelligence systems controlling so many aspects of society raise ethical and privacy concerns. Preventing unauthorized access to sensitive information of both citizens and organizations is important. All digital information is vulnerable to hacking and misuse. Hence, there is a dire need for Artificial Intelligence enabled systems to handle data securely with relevant privacy safeguards. AI involves a lot of expense as it requires the latest hardware and software to remain relevant. As of now, AI capabilities are already limited by the data given to it and it lacks creativity. Unlike humans, AI cannot think of anything new or out of the box. Another disadvantage of AI is that it can make humans lazy. If repetitive tasks, calculations and data analysis are permanently handed over to robots, humans will potentially use their brains lesser and their reactions to any task or event will be sloppy.

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 Keywords

Artificial Intelligence, Autonomous system, Human brain, Unauthorised access, Humanity, etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Baccho ke mansik vikas mein mata-pita aur adhyatm ki bhoomika

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Creative Commons Attribution 4.0 and The Open Definition

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Baccho ke mansik vikas mein mata-pita aur adhyatm ki bhoomika

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Baccho ke mansik swasth pr internet ki bhoomika

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Creative Commons Attribution 4.0 and The Open Definition

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Baccho ke mansik swasth pr internet ki bhoomika

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The integration of blockchain and quantum cryptography into cloud security is poised to revolutionize the way sensitive data is protected in the digital age. Cloud computing, while offering scalable and cost-effective solutions, faces increasing threats from cyberattacks that compromise data integrity and privacy. Blockchain, with its decentralized and immutable ledger system, offers a robust mechanism for securing data by ensuring transparency, traceability, and resistance to tampering. It allows for secure and verifiable transactions, which is crucial for maintaining the confidentiality of cloud-based data. Quantum cryptography, on the other hand, leverages the principles of quantum mechanics to provide ultra-secure encryption methods, making it nearly impossible for attackers to decrypt data without detection. Together, blockchain and quantum cryptography create a dual-layered defense system that enhances both data privacy and security in cloud environments. This combination addresses the growing need for next-generation security protocols to protect against sophisticated cyber threats and quantum computing's potential to break existing encryption methods. This paper explores the synergy between these two technologies, highlighting their potential to safeguard sensitive information, foster trust in cloud services, and pave the way for a secure, data-centric future in the cloud computing era.

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 Keywords

Blockchain, Quantum Cryptography, Cloud Security, Data Privacy, Post-Quantum Cryptography, Zero-Knowledge Proofs (ZKP), Multi-Party Computation (MPC), Quantum Key Distribution (QKD)

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A Critical Analysis of Nathaniel Hawthorne's The Scarlet Letter Abstract: Nathaniel Hawthorne's The Scarlet Letter (1850) is a seminal work in American literature, offering profound insights into themes of sin, guilt, and redemption. This paper critically examines the novel's exploration of Puritan society, its psychological depth, and its symbolic complexity. By analyzing key characters, motifs, and Hawthorne's narrative techniques, this study highlights how The Scarlet Letter remains a timeless reflection on human morality and societal hypocrisy. Introduction: Hawthorne's The Scarlet Letter is set in 17th-century Puritan Massachusetts and revolves around Hester Prynne, a woman condemned to wear a scarlet "A" as punishment for adultery. The novel delves into themes of sin, punishment, and identity while critiquing the rigid moral codes of Puritan society. This paper aims to explore the novel's psychological depth, its symbolic elements, and its critique of oppressive social structures. Theme of Sin and Redemption: The novel presents a nuanced view of sin, showing how individuals respond differently to guilt and shame. Hester Prynne transforms her punishment into a symbol of resilience and grace, while Arthur Dimmesdale, her secret lover, suffers privately under the weight of his concealed sin. Roger Chillingworth, Hester's estranged husband, represents vengeance and the destructive power of unbridled obsession. Through these characters, Hawthorne illustrates how sin can lead to both destruction and redemption. Symbolism in The Scarlet Letter Hawthorne employs rich symbolism to enhance the novel's thematic depth. The scarlet letter itself evolves from a mark of shame to a symbol of strength and defiance. Pearl, Hester's daughter, embodies the living consequence of sin but also serves as a force of truth and transformation. The forest represents freedom and natural law, standing in contrast to the rigid structures of Puritan society. These symbols reinforce Hawthorne's critique of societal norms and the complexities of human nature. Puritan Society and Hypocrisy: Hawthorne's portrayal of the Puritan community reveals its inherent contradictions. While society claims to uphold morality and justice, it often fosters hypocrisy and cruelty. The public shaming of Hester contrasts with the hidden sins of figures like Dimmesdale, highlighting the discrepancy between appearance and reality. Hawthorne suggests that true morality is not dictated by rigid laws but by individual conscience and empathy. Narrative Style and Psychological Depth: Hawthorne's use of a third-person omniscient narrator allows for deep psychological exploration of his characters. His introspective and descriptive style immerses readers in the moral dilemmas faced by Hester, Dimmesdale, and Chillingworth. Through internal monologues and symbolic imagery, the novel captures the torment of hidden guilt and the complexities of human emotions. Conclusion: The Scarlet Letter remains a powerful exploration of sin, identity, and societal oppression. Hawthorne's masterful use of symbolism, psychological depth, and critique of Puritan values make the novel a timeless piece of literature. By examining how individuals confront their past and seek redemption, The Scarlet Letter continues to resonate with contemporary readers and scholars alike.

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 Keywords

Keywords: The Scarlet Letter, Nathaniel Hawthorne, sin, redemption, Puritan society, symbolism, morality, psychological depth

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 Abstract

The Fertilizer Industry is one of the most and core industry in India. In India there are many large and developing industries (Crude oil, Coal, Refinery, Cement, Textile, Steel, FMCG, Agriculture) and has significant contribution to GDP of India. The main Objective of the study is to analyse the Working Capital Management Ratios and Net Profit Margin of company during the study period is 2019-20 to 2023-24. Data Collection is based on secondary data collection method. Sample Selection is judgemental non parametric sampling method is used. For Data Analysis ANOVA test is applied for Analysis of Working Capital Ratios and NPM, Correlation is used to know the relationship between Working Capital and Profitability and Regression is used know the how many impact is working of Working Capital on Profitability for selected companies. Findings is that are is no significant impact of Working Capital on Profitability.

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CR- Current Ratio, QR- Quick Ratio, ITR- Inventory Turnover Ratio, CashR- Cash Ratio, NPM- Net Profit Margin, WCM- Working Capital Management

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This survey explores the evolving landscape of adversarial attacks on neural networks, with a focus on sponge attacks, which exploit the efficiency mechanisms of multi-exit networks (MENs) to maximize energy consumption and inference latency without degrading classification accuracy. Sponge attacks pose significant challenges to real-time applications like autonomous systems and healthcare diagnostics by negating the computational efficiency of MENs. Additionally, the survey examines the broader context of adversarial and backdoor attacks, such as data poisoning, which target model integrity during training. Recent advancements in defensive mechanisms, including certified defenses against poisoned data, defensive data augmentation, and anomaly detection, are analyzed for their effectiveness in addressing these threats. The role of real-time attack response systems (RTARS) and multi-exit architectures in mitigating latency-based attacks is also explored. Key findings highlight that while anomaly detection and pre-filtering techniques provide foundational security, gaps remain in handling hybrid and evolving adversarial threats like sponge poisoning. This survey concludes by identifying the necessity of integrating hybrid detection mechanisms--combining anomaly detection, real-time monitoring, and data augmentation--to enhance the robustness of neural networks against sponge attacks and other adversarial challenges, ensuring secure and efficient deployment in critical applications.

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 Keywords

Anomaly Detection, Defensive Data Augmentation, RTARS, Neural Networks, Machine Learning.

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Creative Commons Attribution 4.0 and The Open Definition

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The Indian e-commerce sector has witnessed rapid expansion with the advent of digital marketplaces, leading to challenges in demand forecasting and inventory management. This study aims to predict product demand using time series models such as ARIMA, TBATS, and Autoregressive Neural Networks (AR-NN). Historical sales data from Indian e-commerce platforms is analyzed to identify trends, seasonal variations, and demand fluctuations. The models are evaluated based on Root Mean Square Error (RMSE) to determine their forecasting accuracy. The results indicate that ARIMA performs best for stable seasonal patterns, TBATS for irregular trends, and AR-NN for non-linear demand fluctuations. This research provides valuable insights for Indian e-commerce businesses to optimize inventory management, enhance supply chain efficiency, and improve overall customer satisfaction.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ARIMA, TBATS, Artificial Neural Network (AR-NN), Time Series Forecasting, E-commerce Demand, Inventory Optimization, Indian Market, Predictive Analytics, Machine Learning in Retail, Supply Chain Forecasting, Seasonal Demand Prediction, Consumer Behavior Analysis, Retail Sales Forecasting, Data-Driven Decision Making, Demand Planning, E-commerce Logistics, AI in Demand Forecasting, Business Intelligence in Retail, Sales Trend Analysis, Deep Learning for Demand Estimation.

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Focus of the researcher in present investigation was to understand about the contribution of velocity of the run-up and power of leg muscles on performance of horizontal jump as those are most influential factors to achieve the higher performance level in competition. To fulfill the purpose, 30 male district level horizontal jumpers were selected as subjects from different coaching clubs of North 24 Parganas, South 24 Parganas and Kolkata district of West Bengal for the present study. Their age were ranged from 12 to 14 years. Velocity of the run-up, power of leg muscles and performance of horizontal jumpers were measured through time of run up, Hop test and Running Broad Jump respectively. In order to analysis the data and find out the relationship, Pearson product moment correction of coefficient was applied. Further Multiple Correlation was applied to find out the combined effect of velocity of the run-up and power of leg muscle on performance of horizontal jump. Level of significance was set at 0.05 level. The researcher found significant relationship between velocity of run-up & performance in horizontal jump and also between the power of leg muscle & performance in horizontal jump. Researcher also noted that velocity of run-up and power of leg muscle both has a combined effect on performance in horizontal jump.

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 Keywords

Key words: Velocity of run-up, Power and Horizontal jump.

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Creative Commons Attribution 4.0 and The Open Definition