Volume 14 | Issue 2 |

 Abstract

The project "AI-Powered Tender Flow and Procurement Optimization System" will provide a new smart, fully-automated platform for the entire tender cycle from tender creation to tender evaluation and award. Artificial Intelligence (AI) models will be used to develop semantic tender search, intelligent bid comparison and anomaly detection to identify fraudulent or unrealistic bids. Real time updates and notifications are enabled by using Socket.IO to ensure instant communication between tender owner and bidder. Secure and separated access for all interested parties is ensured by role based access control. The frontend will be developed as an application based on Next.js and React. In addition, the backend will be developed with Node.js and Express.js as well as a MongoDB database to securely store all data and for analysis purposes. A completely manual free of errors, risk-reduced procurement process with enhanced confidence in all parties involved, will be realized by this system. Additionally, performance and scalability will be demonstrated through a successful cloud deployment and load test.

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 Keywords

AI-Powered Procurement, Tender Management System, Semantic Search, Bid Intelligence, Anomaly Detection, Real-Time Collaboration, Transparent Procurement

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 Abstract

Dermatological disorders impact roughly one-third of humanity, creating substantial healthcare burdens through physical symptoms and emotional distress. Diagnosis timing presents critical obstacles stemming from inadequate specialist availability, expensive medical consultations, and prolonged scheduling delays. Our work introduces an artificial intelligence driven analytical platform employing hierarchical convolutional architectures for automated pathological identification. This framework operates through dual-phase methodology: initial broad categorization followed by granular sub-classification refinement. Through exploiting pre-trained EfficientNetB3 architecture, our implementation demonstrates 81% primary-level precision across 3 broad categories (infectious, inflammatory, others) encompassing 23 disease classes and 62% secondary-level precision for fine-grained classification, achieving 71% overall accuracy after complete integration. The browser-based platform delivers instantaneous diagnostic assessments incorporating probability metrics and therapeutic guidance. Cloud-enabled model training through Google Colab facilitates efficient development eliminating specialized computing requirements, establishing an accessible screening mechanism particularly valuable for medically underserved communities

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 Keywords

Hierarchical CNN, Skin Disease Classification, Transfer Learning, Deep Learning, EfficientNetB3, Medical Image Analysis, Web-based Healthcare

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Rural marketing in India involves tailored strategies to reach diverse rural consumers by understanding their unique needs and purchasing behaviours, which are influenced by factors like community opinion, seasonal income, and a focus on value for money. The main objectives of this study are to study the rural marketing activities of companies and government initiatives to develop rural marketing activities and to analyse the green marketing practices of companies in the present days. The source of this study is limited to secondary sources, in this research extensive review of existing literature and websites information are considered analyse and interpret. Opportunities in Indian rural marketing include a vast untapped market, rising incomes, improved infrastructure, and increasing digital penetration. These factors have created demand for a wide range of products, from agricultural inputs to durable goods and FMCG, making rural areas a significant growth area for companies seeking to escape saturated urban markets. Rural marketing in India faces challenges like poor infrastructure, low literacy, income sensitivity, and cultural/language barriers, but also presents opportunities such as a large untapped population, rising literacy, increasing purchasing power, and the potential for innovative digital strategies.

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 Keywords

rural marketing, companies, Government initiatives, rural marketing activities

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Creative Commons Attribution 4.0 and The Open Definition

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The increasing adoption of Internet of Things (IoT), wearable sensors, and telemedicine platforms has transformed healthcare data generation from batch-oriented records to continuous real-time streams. While Big Data Analytics (BDA) frameworks have demonstrated value in retrospective healthcare analysis, their batch-centric design limits timely decision-making, particularly in developing healthcare systems such as India. In parallel, large-scale real-time data collection intensifies ethical, privacy, and governance challenges related to consent, secondary data use, and regulatory compliance. This paper investigates the convergence of real-time Big Data Analytics and ethical data governance within the Indian digital healthcare ecosystem. A layered real-time analytics architecture is proposed to support streaming healthcare data from IoT devices and remote monitoring systems while embedding governance mechanisms aligned with Indian regulatory initiatives. The study highlights gaps in existing batch-based analytics models, analyzes ethical risks across healthcare datafication layers, and proposes governance controls to ensure responsible data usage. The findings demonstrate that integrating real-time analytics with ethical-by-design governance is essential for scalable, trustworthy, and patient-centric digital healthcare in India.

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 Keywords

Real-Time Big Data Analytics, Digital Healthcare, Data Governance, IoT Healthcare, Ethics and Privacy, Indian Healthcare Systems.

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Global commercial services export comprises transport, travel, and goods-related services. Goods-related services include maintenance, repair, and manufacturing services. The paper analyzes goods-related services exports from 2005 to 2024, by utilizing secondary data from the WTO and demonstrating pictorial representations for comparison. The Revealed Comparative Advantage (RCA) Index indicates a country's export specialization, with values greater than one demonstrating a competitive advantage. Between 2012 and 2023, world exports of goods-related services grew significantly, led by China, South Asia with India and ASEAN countries also experiencing noticiable increases. Factors driving growth include digital transformation, logistics advancements, and the rise of India's IT sector. The upward trend in services exports indicates a transition towards high-value services across the region, with continued resilience in spite of facing the challenges like the COVID-19 pandemic. Exporting goods-related services is vital for India and its neighbouring countries as they can make transition from developing to developed economies. China, Bangladesh, Malaysia, Myanmar, Singapore, and the Philippines display a competitive edge in these exports, leveraging their integration into global value chains (GVCs), cheap-cost labor, improved logistics, and foreign direct investment (FDI). India, Indonesia, Mauritius, and Pakistan face challenges, including high logistical costs, regulatory complexities, and underdeveloped infrastructure, and as a result have revealed comparative advantage (RCA) below 1. Obstacles such as non-tariff measures, technical standards, and lengthy customs processes affect exports, particularly from India and South Asia. Recommended remedial measures include reducing the non-tariff barriers, improving infrastructure, and digitizing customs in order to facilitate trade.

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 Keywords

Export , Services ,Goods -Related ,RCA

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Creative Commons Attribution 4.0 and The Open Definition

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In traditional and modern techniques herbal drugs have been widely utilised due to their therapeutic potential and safety profile. However, their clinical application is often limited because their poor solubility, low bioavailability, chemical instability, rapid metabolism, and lack of site-specific delivery. And in order to overcome these limitations, nanotechnology enabled novel drug delivery systems (NDDS) has emerged as a promising strategy to enhance the therapeutic performance of herbal formulations. This review article provided a comprehensive overview of NDDS employed for herbal drugs, focusing on their design strategies, their mechanism of action and clinical relevance. Various carrier systems such as liposomes, phytosomes, nanoparticles, nano emulsions, microspheres, hydrogels, transdermal patches, plant-derived nanovesicles etc. are discussed with representative examples of clinically important phytoconstituents which includes curcumin, silymarin, resveratrol, and epigallocatechin gallate. Additionally, recent advances in marketed formulations, translational challenges, regulatory concerns, and safety considerations are critically examined. The review article also highlights future perspectives, emphasizing green nanotechnology, personalized medicine, and AI-assisted formulation designs too. Overall, nanotechnology-based NDDS offer significant potential to bridge the gap between traditional herbal medicine and modern clinical therapeutics.

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 Keywords

Herbal drugs; Novel drug delivery systems; Nanotechnology; Nanocarriers; Phytosomes; Liposomes; Nanoparticles; Bioavailability enhancement; Clinical translation

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract The cultural richness and strong social cohesion found in India's Northeastern states demonstrate that well-being is deeply rooted in community life, identity and collective resilience. These social and cultural strengths provide a vital blueprint for achieving the broader goals of Viksit Bharat 2047, where development is not measured by economic growth alone but by the holistic well-being, inclusiveness, and sustainability of society. Cultures play a foundational role in shaping social cohesion and collective well-being within increasingly diverse societies. As communities experience rapid social change driven by globalisation, migration, and modernisation, understanding the relationship between cultural practices and social connectedness has become essential. This study uses the concept of social cohesion, cultural and community well-being to understand how culture helps bring people together. This paper has three main objectives. First, it aims to study how cultural practices in the North-eastern states of India promote social cohesion and contribute to community well-being. Second, it seeks to identify the challenges and barriers that affect the relationship between cultural diversity and social cohesion in contemporary society. Third, the paper attempts to understand how strengthening cultural inclusion and social cohesion can support the goals of Viksit Bharat 2047, particularly in promoting inclusive development and social harmony. The study also highlights that while cultures can serve as a powerful unifying force, it can also become a source of divisions when cultural identities are ignored, misunderstood or marginalised. The impact of cultures on social cohesion largely depends on how cultural differences are perceived, the level of mutual respect within society and the nature of state policies toward cultural diversity. The findings highlight the need for inclusive cultural policies and a platform for intercultural dialogue to strengthen social cohesion and promote collective well-being.

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Social cohesion, Community, Well-being, challenges, Cultural diversity, legal Framework Viksit Bharat 2047

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Directional wireless communication systems require efficient power control and accurate alignment to ensure reliable connectivity and optimal energy usage. Conventional optimization-based methods struggle in highly dynamic environments with mobility and channel uncertainty. This paper presents an Artificial Intelligence (AI)-driven framework for adaptive power control and alignment detection. Reinforcement learning is employed to dynamically regulate transmission power, while deep learning models are used to detect alignment states directly from received signal features. Simulation results demonstrate im proved energy efficiency, higher throughput, and robust alignment performance compared to traditional techniques, highlighting the effectiveness of AI-based solutions in next-generation wireless networks Reinforcement learning is utilized to continuously learn optimal transmis sion power policies based on real-time channel conditions and interference levels, enabling improved energy efficiency without relying on explicit channel models. In parallel, deep learning models are employed to identify alignment states directly from received signal fea tures such as signal strength, phase variations, and mobility patterns, thereby reducing beam training overhead and alignment latency. The joint optimization of power control and alignment detection allows the system to adapt more effectively to dynamic wireless envi ronments. Simulation-based evaluations demonstrate that the proposed AI-driven approach achieves higher throughput, lower power consumption, and improved alignment robustness when compared to traditional methods. The results highlight the potential of AI algorithms as a key enabler for next-generation wireless networks, including millimeter-wave and mas sive MIMOsystems, where adaptability and efficiency are critical performance requirements.

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 Keywords

Artificial Intelligence, Adaptive Power Control, Alignment De tection, Reinforcement Learning

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The paper will explore the connection between multilingual education and learning outcomes in contemporary India and the thesis that language is at the center of defining how students learn, engage and succeed in classrooms. Based on the studies conducted in the cognitive field, sociolinguistics and recent debates around educational policies, the paper examines the ways in which teaching using familiar languages can promote conceptual clarity and lower cognitive barriers in the early learning process. It also examines how language plays part in classroom inclusion and provides an analysis of how linguistic recognition affects student confidence and engagement. As multilingual education is gaining promotion in the policy sector, the article reveals the disjuncture between the policy vision and classroom practice especially on how teachers are prepared, availability of resources, and social expectations of English-mediated education. The discussion does not make English an antithesis of multilingualism, but an opportunity that will be more effective when it is established with proper base learning in common languages. The paper proposes a balanced multilingual approach by reinventing understanding of learning outcomes to be based on more than examination scores, to encompass understanding, involvement and linguistic confidence, in order to match the reality of language-linguistic experience of the students. The paper has concluded that multilingual education provides a viable avenue to more significant and fair learning outcomes in the given case that the implementation is underpinned by consistent pedagogical ideas.

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Multilingual Education and the Dynamics of Learning Outcomes in Modern India

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The Prajamandal Movement in Sonepur Estate of Western Odisha emerged as a powerful expression of popular resistance against the autocratic rule of the Garjat princely states under British paramountcy. In Sonepur, the peasantry suffered under oppressive land revenue systems, arbitrary taxation, and forced labour practices such as Bethi, Rasad, and Salami. Civil liberties were absent, and the rulers exercised unchecked authority in internal administration. The situation worsened during the reign of Maharaja Sudhansu Sekhar Singh Deo (1937-1947), when illegal exactions and administrative repression intensified. Inspired by the spread of nationalist ideas and the activities of the States Peoples' Conference, local leaders like Dolamani Dash of Turum village mobilized the rural population to organize resistance against feudal oppression. In October 1938, the Sonepur Prajamandal was formally established to demand responsible government, abolition of forced labour, reduction of unjust taxes, and the recognition of basic civil rights. The movement quickly gained momentum through public meetings, delegations, and mass participation. However, the state authorities responded with arrests, false prosecutions, bans, and intimidation to suppress the agitation. Despite severe repression, the Prajamandal workers continued their struggle with determination. The renewed phase of agitation in 1947 further weakened princely authority, ultimately leading to the merger of Sonepur with the Province of Orissa in December 1947. The movement thus marked a decisive step toward the end of feudal rule and the establishment of democratic governance in the region.

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 Keywords

Prajamandal Movement, Sonepur Estate, Garjat States, Maharaja Sudhansu Sekhar Singh Deo, Political Awakening in Princely States.

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Creative Commons Attribution 4.0 and The Open Definition