Volume 14 | Issue 5 |

 Abstract

With the exponential growth of social media platforms such as Twitter, Facebook, Instagram, and Reddit, vast amounts of user-generated content are produced every second. Sentiment analysis, also known as opinion mining, is the computational study of people's opinions, sentiments, attitudes, and emotions expressed in text. This paper presents a comprehensive review of sentiment analysis techniques applied to social media data, encompassing lexicon-based methods, machine learning algorithms, and state-of-the-art deep learning architectures. We examine the unique challenges posed by social media text -- including informal language, sarcasm, emojis, code-mixing, and data imbalance -- and survey benchmark datasets commonly used in the field. Furthermore, we explore real-world applications spanning business intelligence, political analysis, public health monitoring, and disaster management. Experimental comparisons of leading models are discussed, and open research directions are identified. Our study demonstrates that transformer-based models such as BERT and RoBERTa currently achieve the highest performance, while hybrid approaches combining linguistic knowledge with neural networks show promising potential.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sentiment Analysis, Opinion Mining, Social Media, Natural Language Processing, Machine Learning, Deep Learning, BERT, Twitter, Text Classification.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The lightning-induced overvoltage phenomenon poses a significant threat to insulation stress and failures in high voltage substations. Although much work has been done to understand the mechanisms of shielding failures (SF) and back flashover (BFO), the cumulative effect of both on overvoltage in substations, especially in the presence of lightning electromagnetic pulse (LEMP), has not been adequately explored in the past. This paper attempts to provide a comprehensive review on the subject by critically examining the phenomenon of lightning induced overvoltage in the context of lightning sources, transmission line behavior, and substation transients. A comparative evaluation of widely used lightning current models and attachment models (Electro geometric Model and Leader Progression Model) is conducted, highlighting their impact on predicted overvoltage levels. The analysis shows that conventional electromagnetic transient (EMT) approaches may significantly underestimate overvoltage due to neglect of LEMP effects, especially in BFO scenarios. Furthermore, the roles of multi-stroke lightning, grounding nonlinearity, and travelling wave interactions are critically examined. The review identifies key limitations in existing modeling approaches, including single-stroke assumptions and lack of integrated system-level analysis. Based on these findings, future research directions are proposed toward high-fidelity, multi-physics modeling frameworks for improved insulation coordination and lightning performance assessment in modern power systems.

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 Keywords

Lightning overvoltage shielding failure CIGRE Current model Heidler Current model back flashover substations insulation coordination Electro-geometric model Leader Progression Model LEMP.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Job Portal is a web-based application developed to streamline the job search process for candidates and the recruitment workflow for employers. In the contemporary digital era, online portals serve as a critical bridge between talent and opportunity. This project focuses on the design and implementation of a user-friendly platform that allows job seekers to explore listings, search using keywords, and filter opportunities across various categories. Developed using a Java Full Stack approach, the system utilizes HTML5, CSS3, and JavaScript for a responsive frontend interface, ensuring accessibility across desktops, tablets, and smartphones. The backend architecture, supported by technologies such as Java and Spring Boot, manages server-side logic and data processing, while a relational MySQL database handles secure data storage for users, job postings, and applications. The final implementation demonstrates how modern web technologies can be integrated into a three-tier architecture to create an efficient, scalable, and interactive recruitment system.

Licence: creative commons attribution 4.0

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 Keywords

Development of a Responsive Job Portal System using Java Full Stack Technologies

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Centralized authentication systems suffer from security risks such as single points of failure, password theft, and privacy leakage. Blockchain-based authentication provides decentralization and trust but faces challenges related to performance, cost, and scalability. This paper presents the implementation of a secure authentication framework combining Zero- Knowledge Proofs (ZKPs) and Multi-Factor Authentication (MFA) to enhance privacy and security. ZKPs enable identity verification without revealing sensitive user data, while MFA strengthens resistance against common attacks. The proposed system utilizes off-chain computation with on-chain verification to reduce latency and gas costs. Experimental analysis demonstrates improved efficiency, security, and user experience. The framework is suitable for applications requiring high security such as banking, healthcare, and IoT systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Blockchain Authentication, Zero-Knowledge Proofs, Multi-Factor Authentication, Privacy Preservation, Off-chain Computation, Smart Contracts, Identity Verification.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents the design and implementation of Wanderlust, a scalable, full-stack travel marketplace developed using the MERN (MongoDB, Express.js, React, Node.js) architecture. The primary focus of the research is on addressing the challenges of data consistency and security in NoSQL-based marketplace platforms.

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Creative Commons Attribution 4.0 and The Open Definition

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Scalable Architecture and Security Implementation in a MERN-Stack Based Travel Marketplace

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Creating a tradition Indian feminist writing is rooted in the long-standing history of resistance against patriarchal regulation of women's bodies, women's identities and women's social mobility. Women's writings in India frequently function as counter-script to the hegemony of cultural scripts, illustrating how systems such as gender, sexuality, caste and domesticity dictate women's lives (Tharu and Lalita 14). This tradition defies traditional representation and redefines literature as a political space in which female subjectivity is audible. In this kind of writing, dissent is not just open rebellion but minor acts of negotiation in everyday life: something which resonates with what Mahmood refers to as "the ordinary practices through which women craft forms of agency" (Mahmood 34).

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

resistance, female subjectivity, hegemony, feminism,

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid expansion of digital technologies, including cloud computing, mobile platforms, and Internet of Things (IoT) ecosystems, has significantly increased the need for advanced security solutions. Conventional methods like passwords and fixed access controls are no longer effective against today's cyber threats, including phishing, stolen credentials, and unauthorized access. Artificial Intelligence (AI) introduces a new paradigm in security by enabling adaptive and intelligent authentication mechanisms. By leveraging machine learning, deep learning, and behavioral analysis, AI systems can evaluate user behavior, biometric characteristics, and contextual information to verify identities in real time. Technologies such as facial recognition, voice authentication, and behavioral biometrics support continuous authentication, improving both security and user convenience. In access control, AI facilitates dynamic and context-aware decision-making by analyzing factors such as user activity, device type, and location. This supports modern security models like Zero Trust, which require continuous verification instead of relying on a single authentication step. This paper examines the role of AI in authentication and access control, outlining its benefits, limitations, and future research opportunities.

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 Keywords

Keywords: Artificial Intelligence, Authentication, Access Control, Machine Learning, Biometrics, Cybersecurity, Behavioral Analytics

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The main motto of presented paper is to know how far demographic and socio economic factors impact on the study. Further, the study is conducted to know the benefits derived from microfinance activities, involvement in income generating activities before and after joining Self Help Groups and impact factors driving women empowerment. Income generating activities of SHG members is critical, as it is going condition the mode of life, savings formation and acquisition entrepreneurship skills.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Empowerment, money lender, savings, environment, performance, employment, awareness, decision making, self confidence, shift.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Fipronil is a common phenylpyrazole insecticide with strong neurotoxic and systemic action. The present study explores its nephrotoxic effect on male albino rat Rattus norvegicus. Sixteen rats were grouped as control, low dose (10 mg/kg BW), and high dose (60 mg/kg BW) and were given fipronil orally for 21 days. Findings revealed a dose-dependent reduction in body and kidney weights. Histopathological analysis disclosed extensive renal injury in treatment groups with glomerular atrophy, tubular degeneration, mesangial enlargement, and vascular disruption. Biochemical profiles revealed marked reductions in kidney tissue protein, carbohydrate, DNA, and RNA content. Increased blood urea nitrogen and serum creatinine further testified to deranged renal function. These results indicate that fipronil causes extensive structural, biochemical, and functional changes in the kidney through oxidative stress and impairment of transport and metabolic processes. The damage was more intensive with the higher dose, indicating definite dose dependent nephrotoxicity. The findings from this research highlight the possible health hazards from long term exposure to fipronil and the need for careful use of such pesticides to avoid renal impairment.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fipronil, Nephrotoxicity, Oxidative stress, Serum creatinine, Blood urea nitrogen

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

E-content as "digitally prepared learning materials designed to facilitate teaching and learning through the integration of text, audio, video, animation, and interactive elements Sharma and Sharma (2012)." Environmental issues such as global warming, deforestation, and resource depletion demand responsible consumer behavior and informed decision-making. In this context, integrating Information and Communication Technology (ICT) into classroom instruction provides innovative opportunities to enhance conceptual understanding. The study adopted an experimental method using a one-group Pre-test and Post-test design. The sample consisted of 42 commerce stream students from Government Girl's Higher Secondary School, Mavelikara, Alappuzha District, Kerala State. An E-content-based Lesson Transcript on Green Marketing was developed and implemented as the instructional intervention. A standardized test measuring Green Marketing awareness was administered before and after the intervention. The collected data were analyzed using Arithmetic Mean, Standard Deviation, and t-test. The findings revealed a significant improvement in students' awareness levels, with the mean score increasing from 10.85 in the Pre-test to 18.90 in the Post-test. The calculated t-value (13.82) was significant at the 0.01 level, indicating that the E-content intervention had a statistically significant effect on enhancing Green Marketing Awareness among Higher Secondary Students.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

E-content, Green Marketing Awareness, ICT in Education

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Creative Commons Attribution 4.0 and The Open Definition