Volume 13 | Issue 3 |

 Abstract

In the evolving landscape of criminal investigations, technology has emerged as a transformative force, revolutionizing evidence collection and law enforcement operations. This study explores the integration of advanced tools such as artificial intelligence, big data analytics, digital forensics, and biometrics in modern policing. By enhancing the speed, accuracy, and credibility of investigations, these technologies address traditional limitations and adapt to the challenges posed by cybercrime and sophisticated criminal activities. Historical milestones, including fingerprint and DNA analysis, laid the groundwork for contemporary advancements such as 3D crime scene reconstruction and predictive policing. Digital forensics now plays a pivotal role in uncovering crucial electronic evidence, while surveillance technologies like CCTV, drones, and facial recognition have expanded investigative reach. However, the ethical implications of these tools, particularly concerning privacy, bias, and data security, require careful consideration. This study also highlights disparities in technological access among law enforcement agencies, stressing the need for capacity-building initiatives. Future trends point toward increased reliance on AI and data-driven policing, demanding stringent ethical standards and transparent governance. Through examining these developments, the study offers policy recommendations to guide responsible technology integration, ensuring that innovation enhances justice while safeguarding civil liberties.

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 Keywords

Criminal Investigations, Law Enforcement, Artificial Intelligence, Big Data Analytics, Digital Forensics, Biometrics, Fingerprint, DNA Analysis and Facial Recognition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Swami Vivekanad ke shaikshik evam darshanik vicharo ka adhyayan

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Swami Vivekanad ke shaikshik evam darshanik vicharo ka adhyayan

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The recent visit of Sri Lankan President Anura Kumara Dissanayake to India highlights the growing economic, political, and strategic ties between the two nations, particularly in the context of Sri Lanka's recovery from its severe economic crisis. This article explores the roots of Sri Lanka's economic difficulties, the role of India in providing critical financial aid, and the strengthening of bilateral relations through development initiatives. The visit also underscores the geopolitical importance of the relationship, particularly in light of China's increasing influence in the region. India's support for Sri Lanka's recovery and its assurances regarding regional security reflect a deeper strategic partnership. Moving forward, both countries aim to enhance cooperation in infrastructure, renewable energy, digital transformation, and maritime security. This evolving partnership holds the potential to contribute significantly to regional stability and prosperity.

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 Keywords

Sri Lanka, India, bilateral relations, economic crisis, financial aid, development cooperation, infrastructure projects, renewable energy, geopolitical influence, China, regional security, India-Sri Lanka partnership, strategic cooperation, maritime security, Sri Lankan recovery, India's foreign policy.

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Smokeless tobacco product (SLT) and Smoking products are available in different brands like Rajnignadha, Vimal, Hira, and RMD (Rasikala Manikchand Dhariwal) cigar manufactured by various smokeless tobacco and smoking tobacco industries. The impact of the use of SLT users and Cigar users on plasma biochemical profile especially the levels of glucose, lipids and lipoprotein patterns, proteins, free amino acids and iron. SLT/smoking tobacco (cigar)-exposure caused permissive but significant effect role by elevating the plasma glucose levels by 12% and 15% in group II and III human exposed subjects respectively when compared to control group I subjects who do not use any SLT/smoking tobacco (cigar) products, there is a net drop in plasma iron, glycolipids with a significant increase in free amino acids. There was no change in HDL-C levels among the three groups. Triglycerides and VLDL-C were significantly elevated in SLT/smoking tobacco (cigar) exposed subjects in group II and III indicating coronary risk.

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Smokeless tobacco, smoking tobacco, Oxidative stress

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Launched in 2023, the Mukhyamantri Ladli Behna Yojana (LBY) in Madhya Pradesh provides direct monthly financial assistance to women with the aim of fostering their economic independence and improving overall socio-economic conditions. This research explores the long-term viability of the scheme's secondary effects, such as increased local market activity, enhanced participation in entrepreneurship, and expanded financial inclusion, in the context of fiscal constraints and growing state-level debt. Employing a mixed-methods approach, the study examines whether these outcomes contribute to sustained economic development or create risks of financial dependency. Findings indicate that LBY has a positive impact on grassroots economic stimulation and women's empowerment; however, its future success hinges on complementary measures like skill development, expanded access to microfinance, and diversified state revenue streams. The study recommends structural reforms to ensure the program's long-term fiscal and economic sustainability.

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Long-Term Economic Sustainability

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Indian social justice scenario in Premchand's fiction: a study

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Indian social justice scenario in Premchand's fiction: a study

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Human sensibilities in the fiction of storyteller Shivani - a study

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Human sensibilities in the fiction of storyteller Shivani - a study

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In today's digital era, the convergence of robust security measures with personalized user experiences is essential for creating trusted digital identity platforms. This study introduces a comprehensive framework that addresses the dual imperatives of safeguarding sensitive information while offering tailored functionalities to meet individual user needs. The framework leverages advanced encryption techniques, biometric verification, and adaptive authentication protocols to mitigate risks without compromising usability. It further integrates machine learning algorithms that analyze user behavior to dynamically adjust security settings, ensuring that the protection level is both context-aware and responsive to emerging threats. By adopting a user-centric approach, the framework empowers individuals to have greater control over their personal data and the manner in which it is shared, thereby fostering a sense of ownership and trust. Additionally, the study discusses the challenges related to interoperability among different digital systems and offers potential solutions that align with global standards. Through iterative testing and real-world applications, the framework demonstrates its capability to reduce instances of unauthorized access while maintaining a high degree of personalization. Overall, the proposed approach not only elevates the security posture of digital identity systems but also enhances the user experience by ensuring that security measures adapt to diverse behavioral patterns and risk profiles. This balance between security and personalization paves the way for more resilient, user-friendly platforms in an increasingly interconnected digital world.

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 Keywords

Digital identity, security, personalization, user-centric framework, adaptive authentication, biometric verification, machine learning.

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Creative Commons Attribution 4.0 and The Open Definition

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Data Governance and Automation Strategies for AI and Cloud Supply Chain Operations represents an emerging paradigm that integrates data integrity with advanced automation to transform supply chain management. This approach emphasizes establishing robust data governance frameworks that ensure the quality, security, and accessibility of data across complex cloud infrastructures. By leveraging artificial intelligence, organizations can enhance decision-making processes, streamline operations, and predict potential disruptions in real time. The synthesis of AI with cloud-based operations facilitates the automation of routine tasks, thereby increasing operational efficiency and reducing human error. Additionally, automated processes support proactive risk management and compliance adherence, which are critical in today's data-driven business environments. This strategy also involves the implementation of dynamic monitoring tools that continuously assess data flows and trigger corrective actions when deviations occur. As supply chains become increasingly global and interconnected, the integration of data governance with automation offers a competitive edge by improving responsiveness and resilience. The seamless coordination between various components of the supply chain is achieved through scalable cloud solutions that support rapid data analysis and integration. Overall, this strategy is not only pivotal in enhancing operational performance but also in fostering innovation within the supply chain ecosystem. Through rigorous governance and state-of-the-art automation techniques, organizations are better equipped to navigate the challenges of digital transformation while maintaining a secure and efficient operational framework.

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Data Governance, Automation Strategies, AI, Cloud Supply Chain, Operational Efficiency, Risk Management, Digital Transformation

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This paper presents an in-depth exploration into the implementation of quality assurance frameworks tailored for AI-driven fraud detection within vehicles registration and titling services. As automotive fraud continues to evolve in complexity, traditional detection methods struggle to keep pace with sophisticated schemes. In response, emerging AI technologies have been deployed to analyze vast datasets and identify anomalies indicative of fraudulent behavior. However, the rapid adoption of these advanced systems has underscored the necessity for robust quality assurance protocols to guarantee accuracy, reliability, and fairness. Our research outlines a comprehensive framework that integrates systematic validation processes, performance metrics evaluation, and continuous improvement cycles. Key elements include real-time data monitoring, cross-verification techniques, and adaptive learning mechanisms that respond to emerging fraud patterns. Through rigorous testing and simulation exercises, the framework has demonstrated its capacity to significantly reduce false positives and negatives, ensuring that only legitimate cases trigger alerts. Additionally, the framework supports compliance with regulatory standards and provides transparency for stakeholders. The study also discusses the challenges of integrating legacy systems with modern AI platforms, addressing potential issues such as data quality, bias in algorithmic decisions, and cybersecurity vulnerabilities. In conclusion, the proposed quality assurance framework not only enhances the overall effectiveness of fraud detection systems in vehicle registration and titling but also contributes to the broader field of AI ethics and governance by promoting accountability and trust in automated decision-making processes.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI-driven fraud detection, quality assurance, vehicles registration, titling services, data validation, continuous improvement, regulatory compliance

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Creative Commons Attribution 4.0 and The Open Definition