Volume 13 | Issue 11 |

 Abstract

This study looks into the strategic roles of tiered influencers, ranging from micro-influencers to celebrities, in shaping modern brand strategies across multiple industries. With influencer marketing becoming a core component of digital communication, brands face a critical challenge in selecting and deploying influencers of varying sizes to meet a wide range of goals, from broad reach to deep consumer engagement. This study investigates how brands use micro- and mid-tier influencers for authenticity, niche targeting, and cost-effective engagement, whereas celebrities are strategically used for mass visibility, aspirational value, and association with premium brand messages. The study employs a mixed-methods approach, integrating primary research through in-person observation and analysis of live influencer campaigns with a thorough secondary literature review. Talent selection, budget negotiation, legal coordination, and post-campaign metric evaluation were all included in the primary research's focus on the full campaign execution process. Both qualitative information on audience sentiment and content authenticity as well as quantitative data like average reel views, engagement rates, and reach were used in the analysis. The results show that a successful influencer strategy is a complex, tiered mix that is suited to particular campaign objectives and brand positioning rather than a "one-size-fits-all" approach. Micro-influencers are perfect for establishing genuine, community-level trust because they continuously showed higher engagement rates and were more economical per engagement. Celebrities, on the other hand, were best at creating aspirational value and instant, widespread visibility for campaigns that emphasized brand stature. The study comes to the conclusion that brands are most successful when they strategically combine these tiers and use data-driven insights to strike a balance between immediate reach and long-term customer trust and emotional connection. By showing that successful campaigns necessitate a shift away from traditional top-line metrics and toward a more comprehensive assessment of content quality, audience relevance, and the strategic synergy between various influencer tiers, this study offers marketers and brands a useful road map. In a competitive digital landscape, brands can create more impactful, scalable, and authentic influencer marketing models that generate both short-term visibility and long-term brand equity by combining operational agility, proactive talent curation, and data-driven planning.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Influencer Marketing; Types of Influencers; Celebrity Endorsement; Brand Strategy; Tiered Influencers

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Parkinson's disease is a long term neurodegenerative disease that progressively impairs motor coordination because of the dopaminergic neurons death in brain. It is hard to detect Parkinson's disease in early stage because of the symptoms appear gradually and overlap with normal aging. Recently, data driven methods have demonstrated the use of measurable vocal changes as a potential marker of the disease. In this work, we build a machine- learning framework to classify Parkinson's patients and healthy people using the voice derived features from publicly available datasets. We applied most of the typical preprocessing steps, such as normalization and oversampling to balance the data and stabilize the model. We coded four supervised learning algorithms, Logistic Regression, Decision Tree, K-Nearest Neighbors, and XGBoost, and then used accuracy, precision, recall, and F1-score to evaluate the four models XGBoost obtains the highest accuracy 94%. The experimental results have shown that the voice based biomarkers and machine learning methods can be used to support early, non invasive screening of Parkinson's disease and can be applied to assistive diagnostic system.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Parkinson's Disease, Machine Learning, Voice Analysis, XGBoost, K-Nearest Neighbors, Logistic Regression, Decision Tree, Biomedical Signal Processing, Early Diagnosis, Healthcare Analytics.

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Creative Commons Attribution 4.0 and The Open Definition

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This paper examines Vidheyan (1994), Adoor Gopalakrishnan's adaptation of Paul Zacharia's Bhaskarapatelarum Ente Jeevithavum, as a critical site for interrogating Christian subalternity, muted masculinities and the politics of representation in Malayalam cinema. Moving away from the dominant screen constructions of the assertive, land-owning Syrian Christian male of the late 1980s and early 1990s, the film positions Thommi--a migrant farmhand in South Karnataka--as a radically atypical Christian protagonist marked by fear, submission, and psychological immobility. Through Thommi's subject-position, the narrative foregrounds the socio-historical experiences of Christian settlers whose identities are shaped by economic precarity, feudal violence, and internalised servitude. The theoretical framework in the analysis includes subaltern studies theory and the politics of representation to argue that the film decodes the subaltern Christian self not through heroic assertion but through a complex affective economy of domination, masochism and muted resistance. By reading Thommi's relationship with Pattelar through frameworks of hegemonic masculinity, Lacanian subject formation, and subaltern theory, the paper demonstrates how the film destabilises triumphalist settler narratives characteristic of Syrian Christian cultural memory. Additionally, the analysis situates Vidheyan within a wider genealogy of Christian representation in Malayalam cinema--tracing contrasts with contemporary depictions in Sangham, Kottayam Kunjachan, and later counter-hegemonic films such as Dany, Achanurangatha Veedu, Ee.Ma.Yau., and O Baby. These comparisons reveal how marginal Christian identities--Latin, Dalit, Anglo-Indian, and migrant--complicate monolithic constructions of Christian masculinity. Vidheyan offers a significant alternative imaginary, where the Christian male emerges not as hegemon but as the "settler other," enabling a rethinking of power, agency, and community within the cinematic public sphere of Kerala.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Subalternity, Christian Masculinities, Malayalam Cinema, Settler Narratives, Hegemonic Masculinity, Politics of Representation, Affective Servitude

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Creative Commons Attribution 4.0 and The Open Definition

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Molecular docking has become a cornerstone technique in structure-based drug design (SBDD), allowing researchers to predict the interaction and binding affinity between a small molecule (ligand) and a biological macromolecule (receptor). Over the past two decades, rapid advances in computational biology, structural genomics, and artificial intelligence have transformed molecular docking into a highly efficient and accurate method for virtual screening, lead optimization, and mechanism elucidation. This review provides a comprehensive overview of the principles, mechanisms, and recent advancements in molecular docking, emphasizing its application in modern therapeutic discovery. It discusses the basic workflow of docking, including target preparation, ligand optimization, binding site analysis, scoring functions, and result validation. Furthermore, recent developments such as flexible docking algorithms, molecular dynamics-coupled docking, and AI-driven predictive models are highlighted for their impact on improving docking accuracy and computational efficiency. The article also explores the role of molecular docking in identifying potential leads against diseases such as cancer, diabetes, neurodegenerative disorders, and viral infections. By bridging theoretical chemistry and pharmaceutical innovation, molecular docking continues to play an essential role in accelerating the drug discovery pipeline and shaping the future of personalized medicine.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Molecular Docking, Drug Discovery, Structure-Based Drug Design (SBDD), Virtual Screening, Scoring Functions, Artificial Intelligence, Molecular Dynamics, Computational Pharmacology, Binding Affinity, Therapeutic Discovery

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Preparation And Evaluation of Herbal-Roll on For the Management of Migraine

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Preparation And Evaluation of Herbal-Roll on For the Management of Migraine

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Illegal parking has become a significant concern in modern urban areas, leading to severe traffic congestion, road safety hazards, and inefficient utilization of public spaces. Traditional enforcement methods rely heavily on manual surveillance and human observation, which are both time-consuming and error-prone. This research introduces a deep learning-based framework for real-time illegal parking detection utilizing the YOLOv5 object detection model. The proposed system integrates computer vision and artificial intelligence to detect and track vehicles parked in restricted zones using live video feeds. The framework demonstrates high accuracy, robustness, and real-time capability under diverse environmental and lighting conditions. Extensive experimentation and evaluation reveal that the model achieves an overall precision of 93%, recall of 90%, and an F1-score of 91.5%. The research further highlights the system's adaptability for smart city environments and discusses its scalability, limitations, and future scope.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Illegal Parking, Deep Learning, YOLOv5, Real-Time Detection, Smart City, Object Recognition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In 2025, India stands as the world's most populous nation with an estimated population of 1.468 billion, accounting for nearly 18% of the global population. Tamil Nadu, as one of India's most socio-economically advanced states, demonstrates a progressive trend in educational inclusivity, particularly among Scheduled Caste (SC) and Scheduled Tribe (ST) communities. The educational statistics for 2022-23, drawn from the Statistical Handbook of Tamil Nadu, highlight the state's sustained commitment to equitable education across all levels from pre-primary to higher education and professional institutions. The pre-primary level, 84,021 SC/ST girl children were enrolled, with SC girls forming the majority (95.8%), indicating early-stage participation yet requiring focused inclusion of ST children. In primary education (Classes 1-5), nearly 5.9 lakh SC/ST girls were enrolled, with 80-90% studying in elementary education institutions, revealing strong engagement in foundational schooling. Overall, Tamil Nadu exhibits a structured yet uneven pattern of educational inclusiveness. The data reveal significant achievements in early education access and gender participation, yet persistent disparities in higher and research-level representation. Enhancing transition support, scholarships, and institutional diversity initiatives--especially for ST and female students--remains essential. The findings affirm Tamil Nadu's role as a model for inclusive education in India, while calling for targeted interventions to ensure equitable outcomes across all educational stages and social groups.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

I24, I25, I28, J15, J16, O15

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cloud computing has moved into the primary focus of the current data storage and processing as it is scalable, flexible and economical. During this period, it is associated with inherent security risks of confidentiality and integrity of information. This paper will discuss encryption and specifically block cipher technique- as a solution to these issues in the cloud-based solution. Three algorithms were compared in terms of performance, security and practical application; they included AES, Blow fish and Two fish algorithm. The prototype was created and tested in the cloud environment to test the methodology. The findings indicate that given a proper selection of algorithm and configuration, it is feasible to attain good data protection without causing enormous overheads to the performance.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Block Cipher, Encryption, Cloud Computing, Cloud Security

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents the design and development of a high-frequency RF-controlled wheeled robot tailored for defense and tactical field applications. The system integrates a diverse set of actuators, sensors, and embedded controllers to enable long-range mobility, real-time surveillance, and missile-launching functionality. The robot employs four Johnson quad-encoder motors for precise locomotion, supported by additional gear motors and TowerPro servo motors for directional and payload control. A GPS module and dual Raspberry Pi cameras--standard and night-vision--provide enhanced navigation and continuous monitoring. Communication is facilitated through a Bluetooth Module wireless transceiver, ensuring stable and secure RF transmission. The architecture incorporates two Arduino Uno microcontrollers, dedicated to motor regulation and missile deployment, respectively, while a Raspberry Pi 3 handles live video streaming. Experimental results demonstrate robust RF communication, lowlatency visual feedback, and modular control performance, validating the robot's effectiveness for remote defense operations.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Unmanned Ground Vehicle (UGV), RF Communication, Arduino Uno, Raspberry Pi 3, Encoder Motors, Servo Motors, Missile Launching System, Real-Time Video Streaming, GPS Module, Ultrasonic Sensors, Defense Robotics, Remote Surveillance

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: The performance of Micro, Small, and Medium-Sized Enterprises (MSMEs) in Bihar from 2017 to 2021 is examined in this paper, with an emphasis on their vital role in the state's economic development. It highlights issues that impede the sector's expansion and competitiveness, such as restricted financial access, subpar infrastructure, antiquated technology, and insufficient market connections. Bihar lags behind states like Uttar Pradesh and West Bengal in terms of growth and job creation, even though the number of MSMEs has been steadily increasing. The study identifies growth prospects through sector-specific initiatives, public-private partnerships, and government support, especially in food processing, textiles, and handicrafts. In order to maximize the sector's potential, the paper recommends specific policy measures and skill development initiatives, emphasizing the significance of enhancing credit access, infrastructure, and technology adoption. In order to address these issues and encourage sustainable MSME growth for balanced regional development in Bihar, it ends with suggestions for evidence-based policies and cooperative initiatives.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

MSMEs, Bihar, Employment, Infrastructure, Technology, Development.

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Creative Commons Attribution 4.0 and The Open Definition