Realities that Persuade: Analysing the Cinema-tography of Girl in the River: The Price of For-giveness Sharmeen Obaid-Chinoy and Rubaru Roshni by Svati Chakravarty Bhatkal
Authors-Devika Nandakumar, Professor Dr. Binu V.S
Keyword-Documentaries, Cinematography, Documentary production, New Documentary.
Abstract-The act of persuasion is an inherent quality of documentaries. The Indian documentaries Amoli: Priceless (2018), directed by Avinash Roy and Jasmine Kaur, and Rubaru Roshni(2019), directed by Svati Chakravarty Bhatkal, navigate the emotions of pain, loss, and reconciliation. These pieces of work mark notable changes in the cinematography of Indian documentaries. Amoli investigates the dark underbelly of child sex racketing in India and how innocent mothers and children are the victims, and Rubaru Roshni is an anthology of tales of people healing through forgiveness in time. Both these documentary films have an emotional take on representing stories. Drawing on Stella Bruzzis theory of new documentary, this paper will look at the changing dynamics of Indian documentary production and its purgation of meaning.
Online Learning and Its Influence on Student Engagement and Academic Performance
Authors-Vijayalaxmi S Suvarna
Keyword-Online learning, internet connectivity, educational resources, technological skills
Abstract-Advancement in technology and internet has revolutionized education. The sophisticated learning management systems and various learning platforms makes online learning more flexible, accessible, offers self-paced study opportunities for learners. In recent years online learning has transformed the landscape of education, offering unprecedented opportunities to learn anytime and anywhere. It connects students and educators across the globe. Online platforms offer a diverse range of educational resources, including interactive multimedia content, virtual classrooms, discussion forms and assessment tools accessible to learners anywhere with an internet connection. The study explores students’ attitudes towards online learning, impact on students’ participation, motivation and overall academic performance. This research investigates the multifaceted perspectives of students enrolled in online courses across different age groups. The study examines factors influencing students’ perception, including technological proficiency, learning preferences and the quality of instruction design and facilitation. It is important to address the challenges in adopting online learning and develop effective strategies to improve the quality of online learning experience for students.
Gendered Oppression and Rebellion in Mahaswta Devis Draupadi
Authors-Assistant Professor Ms. G. Abinaya, Assistant Professor Dr. H. Kalaivani
Keyword-Postcolonial Feminism, Gendered Oppression, State-Sanctioned Violence, Adivasi Resistance, Draupadi Myth Subversion, Sexual Violence as Power, Radical Female Defiance, Mahasweta Devis Activism
Abstract-
Defying Conventions: Autonomy, Morality, and Existentialism in Toni Morrisons Sula
Authors-Research Scholar Mrs. V. Gayathri, Dr. N. Vijayakumari
Keyword-Black female identity, autonomy, gender norms, existentialism, moral ambiguity, female friendship, societal ostracization.
Abstract-Toni Morrisons Sula (1973) is a radical exploration of Black female identity, autonomy, and moral ambiguity within a racially segregated society. By centering on the character of Sula Peace, a woman who defies conventional expectations of marriage, motherhood, and communal belonging, Morrison challenges traditional representations of Black womanhood. Unlike the self-sacrificing maternal figures often found in literature, Sula asserts her independence, embracing an existence free from social constraints. Her rejection of prescribed roles leads to her vilification within her community, reflecting how Black women who defy respectability politics are ostracized. This paper examines Morrisons critique of gender norms, morality, and societal expectations through Sulas character, analysing how the novel deconstructs the binaries of good and evil, stability and chaos, conformity and rebellion. Additionally, it explores the complex female friendship between Sula and Nel, highlighting how patriarchal forces condition women to prioritize male relationships over sisterhood. Morrisons existentialist undertones are also discussed, particularly Sulas rejection of redemption, her embrace of personal freedom, and her defiance in the face of death. By integrating Black feminist thought, existentialist philosophy, and psychoanalytic theory, this study argues that Sula is not merely a novel about rebellion but a profound meditation on self-definition and the price of autonomy. Morrisons portrayal of a woman who refuses to conform, even at the cost of social exile, ultimately forces readers to question whether true liberation can exist within a society that demands obedience.
Ian McEwan's Sweet Tooth: The Enduring Role of the Author
Authors-Research Scholar Ms. V. Jennifer Rani and Assistant Professor Dr. N. Vijayakumari
Keyword-Metanarrative, Ian McEwan, Sweet Tooth, first-person narrative, metafiction
Abstract-Ian McEwan's novel Sweet Tooth uses metanarrative techniques to challenge how we understand literature. These techniques create and break illusions of reality, making us question the nature of fiction. The novel responds to Roland Barthes idea of the death of the author by suggesting a different perspective - the disappearance of the subject instead of the author. This allows the authors voice to survive within the narrative. McEwan explores the purpose of fiction, showing an idealized but fragile view of storytelling. The novel rethinks the roles of the author, subject, and reader, leading to a new understanding of authorship.
A Study on Intelligent System Design
Authors-Syed Arman Ali
Keyword-Intelligent Systems, System Design, Artificial Intelligence, Machine Learning, Neural Networks, Natural Language Processing, Expert Systems, Decision-Making, Knowledge Representation, Automation, Data Analytics, Adaptive Systems, Smart Technologies, System Architecture, Autonomous Systems
Abstract-Intelligent system design has become a fundamental area of research and development in modern computing, focusing on the creation of systems that can perceive, learn, reason, and make decisions autonomously. With the rapid advancement of technologies such as artificial intelligence, machine learning, and data analytics, intelligent systems are increasingly being integrated into various domains including healthcare, finance, transportation, and manufacturing. This study explores the principles, methodologies, and architectural frameworks involved in designing intelligent systems. It examines key components such as data acquisition, knowledge representation, learning algorithms, and decision-making processes. The paper also highlights the role of technologies like neural networks, natural language processing, and expert systems in enhancing system intelligence. Furthermore, it discusses important design considerations such as scalability, adaptability, reliability, and security. Challenges including data quality, system complexity, and ethical concerns are also analyzed along with potential solutions. The study concludes that intelligent system design is essential for developing advanced, autonomous, and efficient solutions that address complex real-world problems.
Security Mechanisms in Modern IT Systems
Authors-Rehan Mustafa
Keyword-Security Mechanisms, Cybersecurity, Encryption, Authentication, Authorization, Firewalls, Intrusion Detection System, Intrusion Prevention System, Identity and Access Management, Multi-Factor Authentication, Zero Trust Architecture, Machine Learning, Threat Detection, Data Protection, Network Security
Abstract-Security mechanisms in modern IT systems are essential for protecting digital assets, ensuring data privacy, and maintaining system integrity in an increasingly interconnected world. With the rapid growth of cloud computing, distributed systems, and internet-based applications, organizations face a wide range of cybersecurity threats such as unauthorized access, data breaches, malware, and advanced persistent attacks. This study provides a comprehensive overview of key security mechanisms, including encryption techniques, authentication and authorization methods, firewalls, intrusion detection and prevention systems, and security monitoring tools. It also examines the role of multi-factor authentication, identity and access management, and zero trust architectures in strengthening system security. The integration of artificial intelligence and machine learning for threat detection and response is discussed as a modern approach to enhancing security capabilities. Furthermore, the study highlights challenges such as scalability, complexity, evolving threats, and compliance requirements, along with strategies to address them. The findings emphasize the importance of implementing multi-layered and adaptive security mechanisms to safeguard modern IT systems effectively.
Machine Learning Techniques for Enterprise Data Analysis
Authors-Tan Jia Hui
Keyword-Machine Learning, Enterprise Data Analysis, Supervised Learning, Unsupervised Learning, Reinforcement Learning, Big Data Analytics, Predictive Modeling, Data Mining, Feature Engineering, Explainable AI (XAI), AutoML, Data Preprocessing, Anomaly Detection, Business Intelligence, Data-Driven Decision Making
Abstract-Machine learning (ML) techniques have become essential tools for enterprise data analysis, enabling organizations to extract valuable insights from large, complex, and diverse datasets. This study presents a comprehensive overview of ML methods applied in enterprise environments, including supervised, unsupervised, and reinforcement learning approaches. It explores how these techniques support tasks such as data classification, clustering, prediction, anomaly detection, and decision-making. The integration of ML with big data platforms and cloud computing infrastructures is examined, highlighting the ability to process high-volume, high-velocity, and high-variety data efficiently. The paper also discusses the role of feature engineering, data preprocessing, and model evaluation in improving analytical accuracy and performance. Real-world applications across industries such as finance, healthcare, retail, and manufacturing are analyzed to demonstrate the practical benefits of ML-driven analytics. Additionally, challenges such as data quality, model interpretability, scalability, and security are critically evaluated, along with emerging solutions like automated machine learning (AutoML) and explainable AI (XAI). The findings emphasize that machine learning techniques are instrumental in enabling data-driven decision-making and enhancing operational efficiency in modern enterprises.