Volume 12 | Issue 5 |

 Abstract

The Unlawful Activities (Prevention) Act (UAPA) has been a subject of contentious debate due to its impact on the principles of justice, particularly concerning bail proceedings. This paper critically examines select bail proceedings under the UAPA, highlighting instances where judicial interpretations have strayed from established legal principles. Through an analysis of cases such as Safoora Zargar's and Asif Iqbal Tanha's, the paper elucidates how the burden of proof has been shifted onto the accused, compromising the presumption of innocence. Furthermore, it explores the inherent ambiguities in UAPA provisions, such as Section 43D(5), which require courts to deny bail based on prima facie belief in the prosecution's case. The paper scrutinizes how vague terms like "conspiracy" and "unprecedented scale" have been used to establish prima facie cases, often circumventing factual scrutiny. Additionally, it discusses how courts have expanded the definition of "terrorism" under the UAPA, potentially encompassing acts of dissent within its ambit. Drawing from cases like Thwaha Fasal vs Union of India and Jyoti Jagtap vs National Investigative Agency, the paper underscores the need for judicial restraint and adherence to constitutional rights in UAPA proceedings. Finally, it delineates contrasting approaches by different high courts, indicating ongoing legal and constitutional battles surrounding the UAPA's application. Ultimately, the paper contends that every UAPA case serves as a pivotal battleground in the struggle against state impunity and underscores the significance of evolving legal precedents in safeguarding individual liberties within the UAPA framework.

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 Keywords

Unlawful Activities Prevention Act, Bail under UAPA, Interpretation of bail

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In contemporary democracies, the conduct of political parties plays a pivotal role in shaping the political landscape and influencing public perception. However, the absence of a unified framework guiding the behavior of political parties often leads to ethical ambiguities, fostering distrust among citizens and undermining the democratic process. This research paper proposes a comprehensive model code of conduct tailored specifically for political parties, aiming to instill ethical standards, transparency, and accountability within their operations. The model code of conduct delineates a set of principles and guidelines designed to govern the behavior of political parties across various aspects of their functioning, including campaign finance, candidate selection, party leadership, and inter-party relations. Drawing upon insights from comparative political systems and existing codes of conduct, the framework integrates best practices and addresses common challenges encountered in contemporary political contexts. Central to the proposed model is the emphasis on transparency and integrity in political financing, advocating for strict regulations to prevent the undue influence of money in electoral processes. Furthermore, the code promotes inclusivity and fairness in candidate selection procedures, fostering diversity and representation within political parties. Moreover, the model code of conduct underscores the importance of intra-party democracy, urging parties to adopt democratic decision-making processes and ensure the participation of members in key organizational decisions. Additionally, the framework advocates for ethical leadership within parties, promoting accountability mechanisms to hold leaders accountable for their actions and decisions. By establishing clear standards of behavior and promoting a culture of ethical governance, the proposed model code of conduct aims to enhance public trust in political parties, strengthen democratic institutions, and ultimately contribute to a more robust and inclusive political system. Implementation of such a framework requires collaboration among political stakeholders, civil society organizations, and governmental bodies to ensure its effectiveness and enforceability. Through empirical research and case studies, this paper evaluates the feasibility and impact of implementing the model code of conduct in diverse political contexts, offering insights into its potential challenges and opportunities for adaptation. Ultimately, the proposed framework serves as a roadmap for fostering ethical conduct and promoting democratic values within political parties, thereby advancing the principles of good governance and citizen engagement in democratic societies.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Model of code of conduct,political party government and Election.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Agriculture holds immense importance in India due to its burgeoning population and escalating food demands, necessitating increased crop yields. However, low crop yields are often attributed to diseases caused by bacteria, fungi, and viruses. Detecting and managing these diseases is crucial, and one effective approach is utilizing plant disease detection methods. Machine learning techniques are particularly promising for disease identification in plants, leveraging data-driven insights for accurate detection. Moreover, deep learning has emerged as a powerful tool in computer vision, offering superior performance in disease detection. This comprehensive review explores various AI-based machine learning and deep learning techniques for plant dis-ease detection. Deep learning, in particular, has shown remarkable success in enhancing performance outcomes across diverse domains. By comparing machine learning and deep learning techniques, researchers have demonstrated the effectiveness of deep learning models in detecting plant diseases from images. Implementing deep learning techniques holds significant potential in mitigating major crop losses by promptly identifying leaf diseases from captured images.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

plant diseases, machine learning, deep learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cloud Atlas by David Mitchell presents a multifaceted narrative structure, spanning centuries and genres, that challenges readers to engage actively with its complexities. Employing reader-response theory, this paper examines how readers interpret and navigate the novel's intricate layers of storytelling, thematic richness, and interwoven narratives. Through an analysis of reader responses, this study explores how readers negotiate the novel's nested structure, thematic motifs, and characters' interconnected lives. It investigates how readers identify with and interpret the novel's themes of reincarnation, interconnectedness, and the power of storytelling. By considering readers' diverse interpretations and reactions, this paper sheds light on the dynamic relationship between text and reader in Cloud Atlas, demonstrating how readers actively participate in the construction of meaning within this multilayered literary work. Gone Girl by Gillian Flynn captivates readers with its unreliable narrators, gripping plot twists, and exploration of identity and deception. Drawing on reader-response theory, this paper examines how readers interpret and engage with the novel's intricate narrative structure and psychological complexities. Through an analysis of reader responses, this study explores how readers navigate the novel's unreliable narrators, suspenseful plot twists, and themes of marriage, media manipulation, and the nature of truth. It investigates how readers identify with and interpret the novel's morally ambiguous characters and their actions. By considering readers' diverse interpretations and reactions, this paper illuminates the ways in which readers actively construct meaning within the suspenseful world of Gone Girl, highlighting the dynamic interplay between text and reader in this enthralling psychological thriller.

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 Keywords

Keywords: Reader Response Theory, Narrative Structure, Readers, Gillian Flynn, David Mitchell.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Generative Artificial Intelligence is like the creative brain behind the scenes in the Metaverse, using smart algorithms to make everything from virtual characters to entire worlds, helping us dive into immersive digital experiences like never before.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Generative Artificial Intelligence, Metaverse, smart algorithms, virtual characters, entire worlds, immersive digital experiences

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

An online exam proctoring system is a software solution designed to monitor and ensure the integrity of online exams. To identify any suspect activity or attempts at cheating during the exam, it usually has features like identity verification, real-time video monitoring, screen recording, and advanced analytics. An abstract for such a system would emphasize its principal features and its contribution to the upkeep of an impartial and safe online testing environment. Robust online proctoring systems have become essential to upholding academic integrity due to the swift transition to online learning and remote examinations. This abstract gives a summary of an online proctoring system that was created to deal with the difficulties associated with conducting tests remotely. A secure and trustworthy examination environment is created by the system by fusing secure identity verification with AI-driven monitoring. To find and identify dishonest behavior, it uses screen surveillance and facial recognition.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Proctoring, Real-Time Video Monitoring, Identity Verification

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Data deduplication in cloud storage is essential for reducing redundancies and bandwidth requirements. However, existing schemes reliant on a trusted key server (KS) suffer from vulnerabilities like information leakage and single-point-of-failure. To address these issues, we propose SED, a Secure and Efficient data Deduplication scheme, integrated into a Joint Cloud storage system. SED facilitates global services across multiple clouds, supports dynamic data updates, and mitigates single-point-of-failure risks. Theoretical analyses demonstrate SED's semantic security and robust anti-attack capabilities. With low computational complexity and overhead, SED effectively eliminates data redundancies, enhancing client-side usability. Comparative evaluations attest to SED's superior performance over existing schemes.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deduplication, cloud

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Punjab is predominantly Agrarian state. Punjab agriculture is known for Green Revolution of the late 1960s and 1970s. Punjab has recorded significant agriculture growth since the period of Green Revolution and known with the title of "India's Breadbasket". Punjab, the most prosperous state in the country until recently, is in the midst of a severe economic crisis. The adaptation of new agriculture strategy limited the state to only two crops, wheat and rice. The use of fertilizers, pesticides, insecticides and fungicides has increased. It has led to depletion of ground water, ecological destruction and forced living under the burden of debt. It leads to extreme poverty and forcing them to commit suicide. The need for agriculture diversification and adopt a pro-people and pro-nature model to address growing poverty, hunger and inequalities in India.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Punjab Agriculture, Green Revolution, Groundwater Depletion, Ecological Destruction

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Creative Commons Attribution 4.0 and The Open Definition

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The exponential growth of electronic waste (e-waste) presents a critical environmental and public health concern globally, necessitating effective management strategies. This study investigates household practices in e-waste management in Tambaram, Tamil Nadu, India, employing a mixed-method approach involving primary data collection through questionnaires and secondary data analysis. The research aims to evaluate awareness levels and current practices among Tambaram residents regarding responsible disposal methods and to propose sustainable strategies tailored to community needs. Findings reveal a correlation between household income and electronic purchasing behavior, with a significant segment possessing considerable purchasing power. Despite the prevalence of unused electronic items in households, proactive measures such as promoting recycling programs and raising awareness are imperative. Most households tend to retain unused electronics at home or dispose of them with regular waste, emphasizing the need for educational initiatives and convenient disposal options. Concerns about the environmental impact of e-waste disposal are prevalent, yet awareness of recycling programs remains inadequate. However, a majority express willingness to modify disposal habits to mitigate environmental impacts, suggesting a potential shift towards sustainable practices. The study underscores the urgent need for enhanced education, infrastructure development, and community engagement to address the challenges associated with e-waste accumulation effectively. By offering insights and recommendations, this research contributes to the development of targeted interventions for responsible e-waste disposal and recycling in urban and semi-urban areas.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

: E-waste management, Household practices, Awareness, Recycling, Sustainability

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's knowledge-based economy, investors and stakeholders place significant value on IP assets when evaluating startup opportunities. A robust IP portfolio not only demonstrates the uniqueness and market potential of a startup's offerings but also provides assurance to investors regarding the startup's ability to protect its innovations, establish market presence, and generate sustainable revenue streams . This paper aims to provide startups with comprehensive insights, strategies, and best practices for effectively protecting their IP assets to enhance their chances of securing funding. By understanding the nuances of IP protection, leveraging IP for competitive advantage, navigating IP challenges in fundraising and building a winning IP protection strategy, startups can position themselves strategically in the investment landscape and unlock opportunities for growth, innovation, and market leadership.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Intangible assets, including patents, trademarks, copyrights

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Creative Commons Attribution 4.0 and The Open Definition