Volume 13 | Issue 4 |

 Abstract

The proliferation of deceptive and computer-generated reviews constitutes a major challenge in e-commerce, social media, and digital marketing domains. To address this critical issue, the current work introduces an innovative ensemble-based methodology integrating linguistic analysis and reviewer behavioural profiling for accurate differentiation between authentic and fabricated textual reviews. Employing a diverse dataset comprising real and artificially generated reviews and using an ensemble of Logistic Regression, Random Forest, and Long Short-Term Memory (LSTM) networks collaboratively analyse linguistic patterns indicative of fraudulent textual review. Complementing textual analysis, a novel meta-feature engineering strategy assesses reviewer credibility through parameters such as review frequency, rating variance, and burst activity metrics. This meta-data-based approach simultaneously finds reviewer authenticity probabilities as new reviews are posted, indicating evolving behavioural patterns. The system computes an integrated probability score, effectively combining textual and meta-behavioural data. Overall evaluation demonstrates robust performance, effectively capturing emergent spam behaviours in real-time. The proposed methodology shows significant potential for practical deployment in automated moderation, digital content verification, and online fraud prevention applications.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fake review detection, Ensemble modelling, LSTM, Behavioural meta-analysis, Dynamic classification

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

When fuel prices rise and environmental pollution turns into a crying need, hybrids have become an economically viable substitute for conventional gasoline cars. Hybrid technology combines electric motors and internal combustion engines to provide efficiency with low emissions. The present research effort tries to investigate the extent of awareness and satisfaction of hybrid car owners within the city of Coimbatore. It formulates the main determinant factors, disadvantages, and extent of increase in adoption by consumers.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hybrid Cars, Fuel Efficiency, Customer Satisfaction, Awareness, Green Mobility.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid growth of e-healthcare, fueled by IoT devices and wearables, has introduced significant privacy challenges, particularly in securing sensitive patient data collected and transmitted across distributed environments. To address these concerns, a novel Nomadic Agent System (NAS) architecture is proposed, combining edge computing, a central node with Kafka-based request management and ElasticSearch data indexing, and cloud storage. This architecture aims to enhance privacy protection by leveraging advanced technologies to secure data at multiple levels. A key innovation is the integration of Large Language Models (LLMs) within the nomadic agents at the central node, which are employed to improve data anonymization techniques. By utilizing LLMs, the system provides a more robust defense against re-identification attacks, ensuring that sensitive patient data is anonymized effectively while remaining usable for analysis and decision-making. The NAS architecture operates across multiple layers, with edge computing handling data collection and preprocessing, the central node managing data requests and indexing, and cloud storage ensuring scalable and secure data retention. The use of Kafka and ElasticSearch at the central node enables efficient data processing and retrieval, while the LLM-based anonymization process adds an additional layer of privacy protection. Potential benefits of this approach include enhanced data security, improved anonymization, and scalability for large-scale e-healthcare systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

E-healthcare, Privacy, Nomadic Agent, Edge Computing, Anonymization, Large Language Models, Kafka, ElasticSearch

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's dynamic and digitally-driven work environments, effective workforce management is critical to organizational success. Traditional systems often face challenges such as data tampering, lack of transparency, delayed processes, and vulnerability to fraud. A blockchain-based workforce management and tracking system addresses these challenges by leveraging the core principles of blockchain technology--decentralization, immutability, and transparency. This system integrates key human resource functions such as employee tracking, attendance monitoring, payroll processing, and task management into a secure, tamper-proof digital platform. Smart contracts are employed to automate routine processes, such as salary disbursement upon task completion or attendance verification, significantly reducing administrative overhead and minimizing human errors. The decentralized nature of the blockchain ensures that data cannot be altered retroactively, enhancing trust among all stakeholders. Employers gain real-time visibility into workforce activities and performance, while employees benefit from transparent and verifiable records of work, attendance, and compensation. This fosters a more accountable and productive work culture. Moreover, the system improves operational efficiency by reducing the need for intermediaries, enabling faster decision-making, and supporting compliance with labor regulations through immutable record-keeping. It is particularly beneficial for industries with large, distributed, or mobile workforces, where traditional HR systems struggle to maintain consistent and secure data management.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Task Management, Decentralization, Smart Contracts, Distributed Ledger, Transparency, Security, Immutable Records, Workflow Automation, Consensus Mechanism, Ethereum(or any specific blockchain platform used), Dapp(Decentralized Application), User Authentication, Access Control, Project Tracking, Task Allocation, Data Integrity, Trustless Environment.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Skin diseases pose significant challenges in the healthcare domain due to their complex and often overlapping symptoms. Early and accurate diagnosis is vital for effective treatment. This paper presents an approach that leverages Convolutional Neural Networks (CNNs) integrated with image segmentation techniques for the classification and detection of skin diseases. The experimental evaluation on publicly available skin disease datasets demonstrates that the model outperforms several existing approaches in terms of accuracy, precision, and recall. This research aims to contribute towards developing a practical tool that can assist dermatologists and medical professionals in automating skin disease diagnosis. Future improvements may include integration with mobile health platforms and expanding the dataset diversity. The proposed methodology underscores the potential of deep learning in medical image analysis, especially for dermatological applications where early detection can make a substantial difference in treatment outcomes.Skin diseases are a growing concern worldwide, requiring early and accurate diagnosis for effective treatment. Traditional methods rely on dermatologists, which can be time consumin. and inaccessible in remote areas. This project proposes an AI-powered skin disease detection system using Convolutional Neural Networks (CNN) and image segmentation techniques. The model processes skin lesion images, applies preprocessing filters, extracts features, and classifies diseases with high accuracy.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI in Healthcare,Skin disease identification,Skin lesion Classification,Medical Image Analysis,Convolutional neural network(CNN),Image Classification,Artificial Intelligence,Pattern Recognition, Feature Extraction,Image Segmentation,Specific Skin Conditions,Image Preprocessing,Shape Analysis.

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Creative Commons Attribution 4.0 and The Open Definition

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This project aims to design and develop an vehicle tailored for industrial and commercial loading applications. As industries shift towards eco-friendly practices, there is an increasing demand for sustainable equipment that can handle heavy loads efficiently while reducing environmental impact. This vehicle is engineered to provide high torque and power output for lifting and transporting materials within warehouses, construction sites, and distribution centers. By incorporating advanced battery technology and energy-efficient motors, the loader ensures extended operational time and minimal emissions. The project encompasses the design, and testing of the vehicle prototype, focusing on load capacity, safety, energy management, and ease of operation to support sustainable, high performance material handling solutions. The development of vehicle equipped with a hydraulic lift is an innovative approach to enhancing the efficiency, sustainability, and adaptability of loading and material handling operations. This design integrates an electric-powered loader with a hydraulic lifting system, providing an eco-friendly alternative. This vehicle is powered by a battery pack, reducing greenhouse gas emissions and reliance on fossil fuels, which aligns with global sustainability goals. The hydraulic lift system allows for precise and robust handling of materials, with the capability to lift heavy loads smoothly and safely. The primary features include a rechargeable battery system, which provides a clean and silent operational environment, and advanced hydraulics for load stability and control. This setup also incorporates energy saving measures, such as regenerative brake which returns energy to the battery during load descent. This vehicle with hydraulic lift offers applications in diverse fields, including construction, warehousing, and manufacturing.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hydraulic lift , trolley system , load handling , DC Motor , Chassis design

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research analyzes the effect of celebrity endorsements on the brand value of nutritional beverages in Coimbatore. It investigates the effects of endorsements on consumer attitudes, brand awareness, loyalty, and purchase intention. Focusing on the youth population, the study assesses the efficacy of endorsements through various media, especially social media. Through a sample of 120 participants, data was analyzed using percentage analysis, Likert scale, and rank analysis. The research indicates that although popularity among celebrities increases purchasing intention and brand recall, product knowledge and credibility contribute more towards influencing consumer behavior and loyalty.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Celebrity Endorsement, Brand Equity, Nutritional Drinks.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Ophthalmic diseases such as cataract, diabetic retinopathy (DR), and glaucoma are leading causes of blindness globally. Early detection and timely intervention are critical to prevent irreversible vision loss. Deep learning (DL), a subset of artificial intelligence, has emerged as a powerful tool in the automatic detection and classification of eye diseases using retinal and fundus images. This review provides a comprehensive overview of recent developments in deep learning methodologies applied to the early diagnosis of cataract, diabetic retinopathy, and glaucoma. We highlight the types of datasets used, popular architectures such as CNNs, transfer learning approaches, evaluation metrics, and limitations. The paper also discusses future directions for research and integration into clinical workflows.

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Creative Commons Attribution 4.0 and The Open Definition

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Early Detection of Cataract, Diabetic Retinopathy, and Glaucoma Using Deep Learning: A Review

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research paper is an analysis of the impact of globalization on the indigenous identity of the ethnic Tharu belonging to the Lakhimpur Kheri district in Uttar Pradesh, India. The Tharu community is rich in cultural heritage, traditional knowledge systems of living, and sustainable livelihood. Under the global economic, social, and cultural currents, this community is undergoing radical changes-it seems as if it were being swept away by a tide. The ethnographic observation, secondary literature review, and comparative analysis have been used to examine the ways globalization factors such as migration, exposure to digital media, education, urbanization, and economic restructuring affect traditional practices, social structures, and self-perceptions within the tribe. The paper thus examines the globalizing process as a doubled-edged sword. Signaling an eclipse of identity through the loss of languages, rituals, and trade-based livelihoods, globalization has also opened new windows for economic mobility, education, and cultural expression via digital platforms. Insights into adaptive strategies and resilience models that can be harnessed for the benefit of the Tharu community are provided by comparative perspectives from other indigenous communities in India (e.g., Gonds, Santhals) and global case studies (e.g., M?ori, Sami). At the close of the study, forward-looking recommendations for cultural conservation, sustainable development, policy reform, and digital empowerment are made. The paper argues, in part, for inclusive governance, bilingual education, and technology-led community engagement in promoting identity resilience under global changes. This approach stresses the importance of indigenous agency.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Globalization, Indigenous Identity, Tharu Tribe, Cultural Preservation, Sustainable Development

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Euthanasia, also known as "mercy killing," has generated a lot of discussion worldwide, and India is not an exception to that. The intentional termination of a person's life to relieve their suffering from terminal or incurable diseases creates serious moral, ethical, and legal issues. Cultural values, belief systems, and the judiciary's dynamic role in interpreting the right to life and dignity have all shaped the legal position of euthanasia in India. Even though the Supreme Court recognised that passive euthanasia is permissible in some situations, there is still substantial controversy around the process of complete legalisation. On the one hand, some contend that letting people choose how they want to pass away is an act of kindness that grants them the freedom to carry out this with honour. On the other hand, opponents warn that legalizing euthanasia might open the door to future misuse and destroy the sanctity of life. This article examines the legal framework, moral dilemmas, and current discussion around the practice of euthanasia in India in order to shed light on the conflicting relationship legal, moral and ethical dilemmas around euthenasia.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Euthanasia, passive euthanasia, active euthanasia, mercy killing,

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Creative Commons Attribution 4.0 and The Open Definition