Volume 13 | Issue 11 |

 Abstract

The rapid escalation of cyber threats, characterized by sophisticated zero-day exploits and polymorphic attacks, mandates a transition from traditional reactive security postures to proactive, AI-driven defense mechanisms. This paper presents a comprehensive systematic review of the state-of-the-art applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in enhancing cybersecurity resilience. We analyze core defensive architectures, focusing on Network Intrusion Detection Systems (NIDS) and advanced malware classification, providing a quantitative comparative analysis of model performance across critical metrics such as Accuracy and Inference Duration. Our findings highlight the superior detection capability of Deep Learning models, specifically Transformer architectures, which achieve up to 98.4% accuracy in NIDS benchmarking. Furthermore, this review critically investigates the dual use challenge, examining emergent adversarial risks, including data poisoning, evasion attacks, and unique vulnerabilities introduced by Generative AI (GenAI), such as prompt injection and the phenomenon of feedback loop security degradation during automated code generation. Finally, we establish the mandate for Explainable AI (XAI) and robust governance frameworks as essential components for ensuring transparency, accountability, and trustworthy deployment of autonomous security systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Intelligence, Cybersecurity, Deep Learning, Network Intrusion Detection System (NIDS), Adversarial AI, Explainable AI (XAI), Systematic Review, Zero-Day Detection.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT: Acne vulgaris remains one of the most common dermatological disorders worldwide, affecting adolescents and adults and significantly impacting quality of life. Although conventional therapies such as retinoids, antibiotics, and hormonal agents are widely used, their limitations--including antimicrobial resistance, skin irritation, high cost, and systemic side effects--have driven increasing interest toward herbal alternatives. Herbal medicines contain diverse phytochemicals such as flavonoids, terpenoids, phenolics, and alkaloids that offer multi-target actions including antimicrobial, anti-inflammatory, antioxidant, and sebum-regulating effects. This review presents a comprehensive exploration of the etiology and pathophysiology of acne, the role of phytochemicals in its management, and the therapeutic benefits of medicinal plants such as aloe vera, neem, turmeric, green tea, tea tree oil, basil, chamomile, calendula, licorice, and rosemary. Emphasis is placed on the scientific evidence supporting their anti-acne potential, mechanisms of action, safety characteristics, and formulation approaches. The review concludes by highlighting current challenges, gaps in clinical validation, and emerging future prospects in integrating herbal therapeutics into mainstream acne management

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Herbal medicine; Acne vulgaris; Natural remedies; Anti-inflammatory agents; Antibacterial phytochemicals; Sebum regulation; Antioxidants; Aloe vera; Neem; Turmeric; Tea tree oil; Green tea; Basil; Witch hazel; Licorice; Rosemary; Chamomile; Calendula; Cutibacterium acnes; Phytochemicals; Dermatology; Plant-based skincare.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

21st sadi mein mahilao ke prati badhte cyber apradh

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

21st sadi mein mahilao ke prati badhte cyber apradh

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

: Amitav Ghosh's Gun Island (2019) presents a powerful literary engagement with climate-induced migration, situating the contemporary ecological crisis within historical and socio-economic contexts. By foregrounding the legacies of colonial exploitation, capitalist expansion, and systemic inequality, Ghosh demonstrates that climate migration is not solely a natural disaster but a human-made crisis. Using postcolonial ecocriticism and the framework of eco-imperialism, this study examines how the novel critiques global environmental inequities, amplifies marginalized voices, and exposes the structural roots of ecological degradation. The blending of myth, history, and contemporary reality underscores the ethical imperatives of planetary stewardship and climate justice. Ultimately, Gun Island exemplifies the capacity of literature to foster ecological consciousness, moral reflection, and collective responsibility, highlighting the urgent need for social and environmental justice in an era of escalating climate crises.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Eco-imperialism, Climate migration, Postcolonial ecocriticism, environmental justice

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract Effective listening is a foundational element of successful communication. While much attention is often given to speaking and writing skills, listening is equally vital, especially in academic, professional, and interpersonal contexts. This paper explores the concept of effective listening, its types, barriers, and role in enhancing communication. It also highlights practical strategies for improving listening skills in various settings. Emphasizing that active and empathetic listening fosters better understanding, collaboration, and problem-solving, the paper concludes that listening is not a passive activity but a powerful tool for meaningful human interaction.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Listening skills, active listening, communication, barriers to listening, interpersonal skills, professional success, effective communication.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Plagiarism detection is a critical task in academic and professional settings. Traditional methods often struggle to identify sophisticated forms of plagiarism, such as paraphrasing and structural reorganization. This paper proposes a novel, multi-stage architecture for an improved and advanced plagiarism checker. Our hybrid model integrates three distinct techniques: (1) an efficient, hash-based document fingerprinting algorithm for initial large-scale screening, (2. a precise string-matching algorithm for detailed syntactic analysis, and (3) a deep learning model with an attention mechanism for capturing semantic similarities. By combining these methods, the proposed system aims to achieve high accuracy and efficiency, effectively identifying a wide spectrum of plagiarism, from literal copying to semantic paraphrasing.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Plagiarism detection, hybrid model, multi-stage architecture, document fingerprinting, Winnowing algorithm, k-gram hashing, hash-based screening, suffix automaton, exact string matching, syntactic similarity, structural reorganization detection, semantic similarity, deep learning, Attention-based Bi-LSTM, neural attention mechanism, text embeddings, paraphrasing detection, contextual analysis, source code similarity, natural language processing, precision, recall, F1-score, semantic plagiarism d

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Women's Economic Independence and Class Struggle in Alka Saraogi's Novels

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Women's Economic Independence and Class Struggle in Alka Saraogi's Novels

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The production and sale of Indian two-wheeler automobiles play a crucial role in the automobile market within India. Two-wheeler automobiles constitute, on an average, 79.5% of total automobile sales in the country since 2001. The average number of two-wheelers per 1000 people in India is 31. India is the second-largest two-wheeler market in the world next to China, with annual sales of about 16 million units in 2022-23. A multiple linear regression model has been adopted to examine the impact of macroeconomic variables on demand for two-wheelers. Ordinary least square method is used to estimate the impact of macroeconomic factors after duly taking care of the assumptions of linearity, normality, multi-collinearity, homoscedasticity and autocorrelation to have consistent and efficient estimates of the regression parameters. The regression model initially considers 13 macroeconomic factors as explanatory variables. After dropping certain macro-economic variables which do not satisfy the tests of linearity, normality, multicollinearity, homoscedasticity and autocorrelation, it is found that per capita income, interest rate of borrowing, vale added in retail trade sector and two-wheeler prices have significant impact on the demand for two-wheelers.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

macro-economic variables, two-wheelers, multiple regression, least square method. Linearity, normality, multicollinearity, homoscedasticity, autocorrelation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study evaluates the financial performance of Indian Overseas Bank (IOB) during the period 2020-2025 using the CAMEL model, which includes Capital Adequacy, Asset Quality, Management Efficiency, Earnings Quality, and Liquidity Position. The study relies completely on secondary data collected from IOB annual reports, RBI publications, and authentic financial portals. Various financial ratios such as Debt-Equity Ratio, Leverage Ratio, Total Investments to Total Assets Ratio, Provision Coverage Ratio, Profit per Employee, Net Profit Margin, and Liquidity Ratios were used to measure the stability, efficiency, and profitability of the bank. The findings reveal that IOB has shown improvement in capital strength, sustained a stable liquidity position, enhanced managerial efficiency, and experienced positive earnings growth throughout the five-year period. The overall analysis highlights that IOB has strengthened its financial health after exiting the PCA framework and has maintained a consistent upward performance trend.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Financial Performance, CAMEL Model, Capital Adequacy, Asset Quality, Management Efficiency, Earnings, Liquidity, Indian Overseas Bank.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Using Machine Learning in CI/CD pipelines brings about specific challenges since models depend on data (data can vary), they evolve over time during the training/exploitation stage (initially a single model is produced for deployment/testing), and the model may require continued training and/or retraining. CI/CD pipelines as they exist today are meant for deterministic code (e.g., non-ML libraries) and do not take into consideration additional important ML system metrics such as data drift and model performance. In this paper, we summarize and highlight the major issues for ML CI/CD implementation, we describe some concrete architecture patterns to deal with identified issues, and give a case study using GitHub Actions and Azure Machine Learning. Results on evaluation show that MLOps based CI/CD has increased ability to release more rapidly, the full pipeline is more reliable, and operationalizing bad models can be avoided.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

machine learning

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Creative Commons Attribution 4.0 and The Open Definition