Volume 14 | Issue 7 |

 Abstract

Insider threats have become one of the most challenging cybersecurity issues, as malicious activities performed by authorized users are difficult to identify using traditional security mechanisms. Conventional log analysis techniques rely heavily on manual inspection and rule-based systems, which are often ineffective in detecting sophisticated attacks and anomalous behavior in real time. This paper presents a blockchain-enabled digital forensic framework for insider threat detection through intelligent log analysis. The proposed system combines Machine Learning algorithms, namely Isolation Forest for anomaly detection and Random Forest for threat classification, with blockchain technology to ensure secure and tamper-proof storage of forensic logs. A Flask-based web application provides real-time monitoring, visualization, and prediction, while an SMTP-based alert mechanism instantly notifies administrators whenever suspicious activities are detected. Experimental evaluation demonstrates that integrating blockchain with machine learning significantly enhances the integrity, reliability, and efficiency of forensic investigations while enabling proactive cybersecurity monitoring.

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 Keywords

Digital Forensics, Blockchain, Insider Threat Detection, Log Analysis, Isolation Forest, Random Forest, Machine Learning, Cybersecurity.

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The relationship between capital structure and financial viability in the banking sector is examined in this essay. In contrast to industrial companies, banks use deposits as a major, special source of credit and are subject to stringent regulatory capital requirements (like Basel III). This study looks at how important profitability indices, particularly Return on Equity (ROE) and Return on Assets (ROA), are affected by the combination of debt, equity, and deposits. According to the analysis, strong equity buffers reduce risk and maintain long-term profitability by lowering the cost of capital, even when more leverage can boost profits during economic expansions

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"An Analytical Study of Capital Structure Vis-a-Vis Profitability of the Banking Industry"

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Diabetes mellitus is one of the most common chronic diseases affecting millions of people worldwide. Early prediction of diabetes helps healthcare professionals provide timely treatment and reduce severe complications. Machine Learning (ML) techniques have emerged as effective tools for disease prediction by analyzing medical datasets and identifying hidden patterns. This paper presents a diabetes prediction system using supervised machine learning algorithms such as Logistic Regression, Decision Tree, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN). The Pima Indians Diabetes Dataset is used for model training and evaluation. Data preprocessing techniques including missing value handling, feature scaling, and normalization are applied to improve model performance. The trained models are evaluated using accuracy, precision, recall, F1-score, and confusion matrix. Experimental analysis indicates that Random Forest provides better prediction accuracy than the other algorithms. The proposed system provides a simple, reliable, and efficient approach for assisting healthcare professionals in the early diagnosis of diabetes.

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 Keywords

Diabetes Prediction, Machine Learning, Random Forest, Support Vector Machine, Logistic Regression, Healthcare Analytics

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M. M. Kaye's The Far Pavilions (1978) occupies a significant position in twentieth-century historical fiction for its imaginative reconstruction of colonial India during the years surrounding the Indian Rebellion of 1857. Combining history, romance, politics, and cross-cultural encounters, the novel has attracted sustained scholarly interest from historians, postcolonial scholars, and literary and feminist critics. Despite this growing body of scholarship, research on the novel remains fragmented, with studies primarily emphasizing historical authenticity, colonial discourse, imperial ideology, and cultural identity. Comparatively fewer studies have critically examined women's representation and the intersection of gender with colonial power. The absence of an integrated review of existing scholarship has created a need for a comprehensive assessment of the critical debates surrounding the novel. The present study undertakes a thematic literature review of major scholarly works on The Far Pavilions published between 1980 and 2025. Using a qualitative review methodology, the study analyses peer-reviewed journal articles, scholarly book chapters, and critical reviews to identify dominant research trends, methodological approaches, theoretical orientations, and existing research gaps. Rather than summarizing previous studies individually, the review synthesizes scholarship into thematic categories, including historical perspectives, colonial discourse, feminist criticism, and postcolonial identity. The review demonstrates that while scholars have extensively explored the historical, political, and cultural dimensions of the novel, comparatively limited attention has been devoted to interdisciplinary analyses integrating feminist literary criticism and postcolonial theory. The study therefore identifies significant opportunities for future research on women's representation, gender identity, and cultural negotiation within colonial historical fiction. By consolidating four decades of scholarship, this review provides a comprehensive foundation for future critical investigations of M. M. Kaye's The Far Pavilions.

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 Keywords

M. M. Kaye, The Far Pavilions, Colonialism, Historical Fiction, Women's Representation, Gender, Identity, Postcolonial Literature, Literature Review.

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Micro-organisms; janapadodhwansa; krimi; bhuta; pretha ; pisaca; raksasa; dravyaguna evidence

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With rising computing demands, data centers produce significant heat loads that must be effectively managed to maintain safe server operation and reduce energy consumption. CFD has become essential in analyzing airflow, thermal distribution, and hot-spot formation in such facilities. Previous research shows CFD can identify thermal issues like hot air recirculation and the importance of containment strategies for efficiency improvements. With the rapid growth of cloud computing and data storage, data centers have become critical infrastructure. However, high heat generation from servers poses a major challenge for efficient thermal management. This project focuses on Computational Fluid Dynamics (CFD) modelling of a 12-rack data center with a total heat dissipation of 500 kW. The objective is to analyze airflow and temperature distribution and determine the maximum temperature for a given CRAC airflow rate. A CFD model is developed using turbulence and heat transfer models to simulate real operating conditions.

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Computational Fluid Dynamics (CFD), Data Center Cooling, Airflow Management, Computational Thermal Analysis, Cold Aisle Containment (CAC)

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Bone defects can develop from different origins like infection, tumor, trauma, surgery, congenital etiology, and so on. Human bones can regenerate and repair themselves, although this ability is limited,regulatory pathway in 3D Printing,Bone component design, manufacturing various types of 3D Printed Bone.

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3D PRINTING,BONE

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Agriculture is an important sector that supports food production and livelihood of millions of people. However, the choice of suitable crop is often difficult for the farmers due to variation in soil and weather from place to place. In order to solve this problem, in this paper, an intelligent decision support system for crop recommendation using machine learning techniques is proposed. The system uses the soil nutrient values like Nitrogen, Phosphorus, Potassium as input features along with temperature, humidity, pH and rainfall. We evaluate several machine learning algorithms, and Random Forest shows the best performance. The system will help farmers to take data based decisions, improve crop selection and increase productivity.

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Artificial Intelligence, Crop Recommendation, Decision Support System, Machine Learning, Precision Agriculture

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Digital payment systems have become an essential part of modern business operations, especially for small scale businesses. The research focuses on understanding the level of awareness, adoption, and usage of digital payment systems such as UPI, mobile wallets, debit cards, and internet banking among small scale business owners. The study also examines how digital payments influence business performance in terms of sales growth, customer convenience, accounting accuracy, and operational efficiency. Primary data were collected from small scale business owners in Shivamaggoa district using a structured questionnaire, while secondary data were gathered from journals, reports, and websites. Simple percentage analysis and tables were used for data interpretation. The findings reveal that digital payments have significantly improved transaction speed, reduced cash handling risks, and enhanced customer satisfaction. However, challenges such as security concerns, technical issues, and lack of digital literacy still affect full adoption. The study concludes that digital payments play a crucial role in strengthening small scale businesses and suggests the need for proper training, awareness programs, and improved digital infrastructure to maximize their benefits. The adoption of these systems helps small businesses improve financial management, reduce operational costs, and increase sales opportunities. However, small business owners may also face challenges such as cybersecurity threats, technological barriers, and transaction fees. Overall, digital payment systems play a significant role in enhancing the efficiency growth, and competitiveness of small businesses in the digital economy.

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Digital payment, UPI Mobile Wallets, Digital Literacy, Modern Business, Cybersecurity threats, Digital Economy.

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Children spend most of their time in school where accidents and emergencies can occur. Teachers are often the first responders; hence, adequate knowledge of first aid is vital to ensure student safety. Many teachers lack sufficient awareness, making it necessary to evaluate and enhance their first aid knowledge through structured programme.

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Creative Commons Attribution 4.0 and The Open Definition

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First aid, knowledge, teachers, emergencies.

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Creative Commons Attribution 4.0 and The Open Definition