Volume 14 | Issue 4

 Abstract

Native advertising has become a vital component of digital marketing strategies, offering a unique opportunity for brands to connect with their target audiences in a non-intrusive manner. By seamlessly integrating with surrounding content, native advertisements can enhance brand awareness, build credibility, and drive consumer engagement. This form of advertising also provides measurable returns on investment and can be tailored to specific audiences and platforms, making it an attractive option for marketers. However, native advertising raises important concerns regarding transparency, ethics, and regulatory compliance. To ensure effectiveness, such advertisements must be clearly labeled as sponsored content, provide relevant and valuable information to the audience, and comply with applicable regulations. When executed effectively, native advertising can create a mutually beneficial outcome for both brands and consumers by delivering meaningful content while achieving marketing objectives. This study examines the effectiveness of native advertising in digital marketing campaigns by analyzing its benefits, challenges, and best practices. It aims to provide insights into how businesses can leverage native advertising to enhance customer engagement, build brand loyalty, and achieve sustainable growth in a highly competitive digital environment.

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 Keywords

Native Advertising, Digital Marketing, Digital Advertising, Content Marketing, Sponsored Content, Brand Awareness, Consumer Engagement, Targeted Advertising, Online Advertising, Marketing Effectiveness

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Sleep and anxiety disorders are extremely popular and co-morbid diseases that greatly deteriorate the quality of life, cognitive abilities, and health in general. The shortcomings of traditional pharmacotherapies, such as adverse effects, tolerance and dependence have resulted in the growing enthusiasm to explore herbal substitutes with superior safety profiles. The purpose of this review is to assess the therapeutic potential of the chosen herbal actives in treating anxiety and sleep disorders, their mechanisms of action, and formulation into form of convenient delivery systems. The databases used in a thorough literature search, including PubMed, Scopus, and Google Scholar, were searched in the period 2000-2025 with the priority on human clinical evidence with preclinical results. Pharmacological effects of key botanicals such as Withania somnifera, Nelumbo nucifera, Ocimum sanctum, Myristica fragrans, and Lavandula angustifolia were studied. These results suggest that these herbal actives have multi-targeted effects such as hypothalamic-pituitary-adrenal axis modulation, GABAergic neurotransmission, serotonergic pathway regulation, and antioxidant activity, which can lead to better sleep and less anxiety. Also, it has been shown that these actives can be incorporated into herbal oral dissolving films (HODFs), showing possible benefits in terms of bioavailability and patient compliance. To sum up, herbal actives are a promising multi-mechanistic treatment to sleep and anxiety disorders, but additional well-designed clinical trials are needed to confirm the effectiveness and standardization of multi-herbal preparations in the wider treatment options.

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 Keywords

: Sleep Disturbance; Anxiety Disorder; Herbal Extract; Nutraceuticals; Oral Dissolving Film

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 Abstract

The rapid expansion of online shopping platforms has significantly increased the variety of products available to users, making the decision-making process more complex and time-consuming. Conventional recommendation systems, such as collaborative filtering and content-based approaches, often struggle to accurately interpret user intent expressed in natural language and typically lack transparency in their outputs. This paper presents a novel design of an AI-driven explainable recommendation system that integrates Large Language Models (LLMs), semantic similarity search using FAISS, and interpretable machine learning techniques such as SHAP. The proposed system is capable of processing user queries in natural language, extracting meaningful preferences, and retrieving contextually relevant products from large datasets. Additionally, it generates clear and human-understandable explanations for each recommendation. By combining advanced language understanding with explainability and efficient retrieval mechanisms, the system improves recommendation accuracy, enhances transparency, and increases user trust. The proposed framework demonstrates the potential of integrating modern AI techniques to build intelligent and usercentric recommendation systems. Index Terms--Explainable Artificial Intelligence (XAI), Recommendation Systems, Large Language Models (LLMs), Semantic Search, FAISS, SHAP, Natural Language Processing (NLP), E-commerce, Personalized Recommendations, Information Retrieval

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 Keywords

Explainable Artificial Intelligence (XAI), Recommendation Systems, Large Language Models (LLMs), Semantic Search, FAISS, SHAP, Natural Language Processing (NLP), E-commerce, Personalized Recommendations, Information Retrieval

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 Abstract

Communication between hearing-impaired individuals and people who do not understand sign language is often difficult. Sign language is the primary method used by deaf and mute individuals to express their thoughts and emotions, but many people are not familiar with it. This communication gap creates challenges in education, healthcare, and daily interactions. The Telugu Sign Language Translator using Deep Learning aims to bridge this gap by automatically recognizing hand gestures used in Telugu sign language and converting them into readable text or speech. The system uses computer vision techniques to capture hand gesture images through a webcam and processes them using a deep learning model. A Convolutional Neural Network (CNN) is trained to identify and classify different Telugu sign gestures accurately. Once the gesture is recognized, the system translates it into corresponding Telugu text and optionally generates voice output using text-to-speech technology. This allows normal users to understand the message conveyed by the sign language user in real time. The proposed system helps improve accessibility and communication for hearing-impaired individuals. By integrating deep learning, computer vision, and speech technologies, the model provides an intelligent and efficient solution for translating Telugu sign language. This technology can be further extended to mobile applications, real-time translation systems, and multilingual sign language recognition platforms. The system is designed to capture hand gestures using a webcam or camera device and process the input images through image preprocessing techniques such as resizing, normalization, and background removal. These processed images are then fed into a trained deep learning model that extracts important features of the hand gestures and classifies them into predefined Telugu sign language categories. The deep learning architecture, primarily based on Convolutional Neural Networks (CNN), is capable of learning complex patterns from gesture images and providing accurate predictions. The recognized gestures are mapped to their corresponding Telugu characters, words, or phrases. The output is displayed as Telugu text on the screen and can also be converted into speech using a text-to-speech module, allowing users to hear the translated message. This system can be highly beneficial in educational institutions, public service centers, hospitals, and workplaces where effective communication with hearing-impaired individuals is essential. By providing real-time gesture recognition and translation, the model reduces dependency on human interpreters and improves communication efficiency. Furthermore, the project highlights the potential of artificial intelligence in building inclusive technologies that support people with disabilities. Future improvements may include expanding the dataset to cover more gestures, improving model accuracy using advanced architectures, supporting continuous sign language sentences, and developing mobile or web-based applications for wider accessibility. Overall, the Telugu Sign Language Translator using Deep Learning represents an important step toward enhancing accessibility, promoting social inclusion, and leveraging modern AI technologies to solve real-world communication challenges.

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 Keywords

Telugu Sign Language, Deep Learning, Computer Vision, Gesture Recognition, Convolutional Neural Network (CNN), Sign Language Translation, Image Processing, Machine Learning, Hand Gesture Detection, Text-to-Speech (TTS), Human-Computer Interaction, Accessibility Technology, Artificial Intelligence, Real-Time Gesture Recognition.

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Abstract -- Android DXFA Data Extraction for Forensic Analysis With the rapid proliferation of Android devices, digital forensic investigations increasingly rely on efficient and reliable data extraction techniques. Android DXFA (Data Extraction for Forensic Analysis) focuses on acquiring, preserving, and analyzing digital evidence from Android systems while maintaining data integrity and legal admissibility. This study presents a structured approach to Android data extraction, encompassing logical, physical, and file system acquisition methods. It examines the role of system artifacts such as application data, call logs, messages, and deleted files in reconstructing user activities. The research also highlights challenges associated with device fragmentation, encryption mechanisms, and evolving security features within the Android ecosystem. Advanced forensic tools and techniques are evaluated for their effectiveness in bypassing security restrictions and extracting hidden or deleted data. Furthermore, the paper discusses the importance of maintaining a proper chain of custody and adhering to forensic principles to ensure the credibility of extracted evidence. The proposed DXFA framework enhances the accuracy and efficiency of forensic investigations by integrating automated extraction processes with analytical methodologies. This contributes to improved incident response, cybercrime investigation, and digital evidence management in modern forensic practices.

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Core Keywords Android forensic data extraction Mobile device forensics Android Logical acquisition Android Physical acquisition Android File system extraction Android Android artifact analysis Android evidence acquisition Mobile forensic workflow ? Android System & Storage Keywords Android file system (EXT4 / F2FS) /data/data directory analysis Android partition layout ADB (Android Debug Bridge) forensic use Rooted vs non-rooted acquisition Bootloader unlocking forensic impact Recovery mode

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Corporate Social Responsibility (CSR) has emerged as a vital strategic tool for organizations, particularly in the banking sector, where public trust and social accountability are of paramount importance. This study examines the perception of Corporate Social Responsibility activities undertaken by the State Bank of India (SBI) in Patna, Bihar, with a focus on understanding awareness levels, sector-wise visibility of CSR initiatives, and their influence on the bank's image, reputation, customer preference, and trust. The study adopts a descriptive and perceptual research design based on primary data collected through a structured questionnaire administered to 424 respondents in Patna city. The data were analyzed using basic statistical techniques, including frequency and percentage analysis. The findings reveal a high level of awareness regarding CSR among respondents, with education and financial literacy emerging as the most visible CSR sectors. The results indicate a strong positive relationship between SBI's CSR initiatives and public perception, demonstrating that CSR significantly enhances the bank's social image, reputation, and trustworthiness. The study also identifies key areas for improvement, including greater publicity, increased funding, better targeting of beneficiaries, and a focus on long-term CSR projects. Overall, the study concludes that effective implementation and communication of CSR initiatives can strengthen stakeholder relationships and support sustainable banking practices.

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 Keywords

Corporate Social Responsibility, Public Sector Banks, State Bank of India, Public Perception, Sustainable Banking.

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This paper focuses on the study and analysis of physical and chemical properties such as viscosity, density of lubricating oils. Standard testing methods and done testing in chemlab laboratory, Pune were used to evaluate the performance of each oil. The results were compared to understand which oil performs better under different operating conditions. This analysis helps in selecting the most suitable lubricating oil for specific applications, which can improve the efficiency and lifespan of machines. The paper aims to provide useful insights for motor vehicles in choosing the right lubricant oil based on performance and comparison of different types of lubricating oils used in engines. Lubricating oils play a vital role in reducing friction, wear, and overheating of moving parts. In this study, we selected several commonly used lubricating oils such as castrol,motul,dynamic+ mental conditions

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 Keywords

Engine oil,lubrication, density,viscosity,performance

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Creative Commons Attribution 4.0 and The Open Definition

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The Smart File Recovery System is an advanced data recovery application designed to retrieve deleted files such as photos, videos, audio, and documents, even after they have been permanently removed from the recycle bin. The system leverages powerful Python-based recovery algorithms combined with intelligent file detection and classification techniques to ensure accurate and efficient restoration of lost data. It scans storage devices at a low level, identifies file signatures, and reconstructs deleted content while maintaining data integrity. The system integrates a user-friendly interface built using HTML, CSS, and JavaScript, ensuring accessibility for both technical and non-technical users. The backend incorporates advanced machine learning and file system analysis to distinguish recoverable data from corrupted or overwritten files, making the recovery process smarter and more reliable. Additionally, the system is compatible with various operating systems such as Windows, Linux, and macOS, offering flexibility and broad usability. This project aims to provide an effective alternative to existing recovery tools by combining automation, accuracy, and simplicity. By integrating intelligent algorithms with an intuitive interface, the Smart File Recovery System enhances the user experience while ensuring high success rates in file recovery. This solution not only helps users retrieve lost files but also contributes to data protection and digital forensics applications.

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Creative Commons Attribution 4.0 and The Open Definition

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The Smart File Recovery System is an advanced data recovery application designed to retrieve deleted files such as photos, videos, audio, and documents, even after they have been permanently removed from the recycle bin. The system leverages powerful Python-based recovery algorithms combined with intelligent file detection and classification techniques to ensure accurate and efficient restoration of lost data. It scans storage devices at a low level, identifies file signatures, and reconstructs

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Crinum latifolium is an ornamental and medicinal plant widely grown in various Indian regions and worldwide. In aurveda, this plant having a significant medicinal importance. In present study, this plant was used in green synthesis of CuO nanoparticles using Copper chloride. However before the green synthesis of CuO nanoperticles, Plant leaves were extracted in double distilled water and methanol. Qualitative phytochemical screening for presence of bioactive compounds and antimicrobial activity against gram negative bacteria (E.coli and Salmonella), gram positive bacteria (K. pneumoniae) and fungi (Fusarium oxysporum) were analysed. After green synthesis of CuO nanoparticles, were characterized using different available techniques UV visible, FTIR and XRD. Moreover about this the synthesized CuO nanoparticles were investigated for antimicrobial potentiality and antioxidant activity.

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Crinum latifolium, Phytochemicals, Antioxidants, CuO nano particles and Antimicrobial activity.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Conventional proctoring systems will typically use secure browsers, or plug-ins, or third-party applications, adding technical complexity, restricting user access, and bringing with them many problems. With the growing popularity of online exams, it has become more difficult to keep academic integrity in remote testing. Physical supervision is absent, and this offers a chance to engage in dishonest behavior, which can be in the form of using secondary devices, communicating with other people, or impersonating others. To overcome these obstacles, a multi-modal online exam proctoring system using AI is proposed in this paper. The system employs a collection of AI methods, such as face recognition, eye-tracking, object recognition, sound analysis, and activity monitoring on social media to deliver real-time monitoring and alert suspected behavior. The proctoring system developed based on the Django framework and MySQL to store data and provide constant authentication during the exam with the minimum disturbance to the user. Any violations detected are stored and displayed on a single main dashboard to the examiners, which offers real-time information and reports. This new type of approach makes online testing more secure, provides online learning with a better experience and provides new prospects regarding the use of AI in the education industry.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Computer Vision, Gaze Tracking, AI-based Exam Monitoring, Multi-modal Monitoring, Online Proctoring, Audio Analysis, Django

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This paper analyzes the plot and thematic issues in the novel The God of Small Things by Arundhati Roy, and how the use of fragmented narration symbolizes the trauma and oppression of caste and the broken identity. Such a non-linear form of the novel reflects the psychological effect of traumatic memories among the characters like Estha, Rahel, Ammu and Velutha. The use of the past and present helps Roy to reveal the violence behind caste hierarchies and patriarchal standards of the postcolonial Indian society. This paper identifies the roles of narrative fragmentation, memory and silence as literary means of expression to show the emotional and social impact of caste-based discrimination and systemic injustice and ultimately constructs identity as being heavily informed by the trauma and structural injustice.

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Caste, Trauma, Identity, Fragmentation, Resistance

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Creative Commons Attribution 4.0 and The Open Definition

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This research paper examines the growth of mutual fund investments in India, driven by factors like diversification, low risk, attractive returns, liquidity, affordability, tax benefits, and transparency. These factors appeal to investors, boosting mutual fund popularity. The paper provides an overview of mutual fund growth in recent years, including inflows into equity and debt funds, as well as SIP contributions. It includes comparative data showing mutual funds' market share relative to other securities, providing a basis for informed investment decisions. Utilizing secondary data from the AMFI website and literature reviews, the study explores mutual funds' appeal and growth potential. It also delves into the industry's challenges, such as market volatility, regulatory compliance, fee structures, and competition from alternative investments. This study explores the factors contributing to the growth of mutual funds, including market accessibility, regulatory support, and technological advances. Additionally, it addresses challenges such as market volatility, regulatory compliance, fee structures, and competition from alternative investment options. By examining these aspects, the study provides insights into the dynamics of the mutual fund industry and highlights considerations for stakeholders aiming to navigate and succeed in this evolving environment. Overall, the paper sheds light on both the drivers and obstacles in the mutual fund sector, offering insights for investors and fund managers in today's financial landscape.

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 Keywords

Mutual funds, Net Asset Value, Equity funds, Debt funds, SIP

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Pouteria campechiana (Kunth) Baehni, locally called canistel or egg fruit, is an evergreen, tropical fruit tree belongs to Sapotaceae family. Traditionally, P. Campechiana has been cultivated for its palatable fruit. Lately, the potential application of P. Campechiana in medicine, especially in its anti-microbial and anti-oxidative properties have received scientists' attention. This review summarizes information from the literature about phytochemical constituents of P. Campechiana and also assess the laboratory findings regarding the anti-microbial and anti-oxidative effect. Highlight is placed on specific compound group like phenolic, flavonoids, carotenoids, and triterpenoids that provide bio-activity of the fruit. Future study needed and limitation of previous investigation were emphasized with the application prospects of the fruit in medicine and nutriceuticals industries

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Pouteria campechiana, canistel, antioxidant activity, antimicrobial activity, phytochemicals, Sapotaceae

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Agriculture in India is highly vulnerable to climatic and production risks which makes crop insurance a crucial policy instrument for income stability of farmers. The Pradhan Mantri Fasal Bima Yojana (PMFBY), launched in 2016, aims in enhancing financial protection and expanding insurance coverage among farmers. This study analyses the performance of PMFBY using an indicator termed Risk Protection Efficiency (RPE), defined as the average benefit received per farmer. The study is completely based on secondary data for both Kharif and Rabi seasons from the official website of PMFBY during the year 2018 to 2025. The study examines trends in loanee farmer participation, benefit distribution and inter-state variations. The results indicate a significant increase in farmer enrolment over time, reflecting expansion of coverage. However, total benefits show fluctuations and RPE exhibits a declining trend in recent years. Seasonal analysis reveals relatively higher RPE in the Kharif season compared to Rabi, while state-level analysis highlights considerable variation in benefit distribution. The findings suggest that as participation expands, benefits are distributed across a larger number of farmers, resulting in lower average benefit per farmer. The study concludes that PMFBY reflects a shift from concentrated benefit distribution to broader coverage, consistent with the principle of diminishing marginal returns. It emphasizes the need for strengthening implementation mechanisms and ensuring proportional resource allocation to enhance the effectiveness of benefit delivery.

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Farmers, Risk Protection Ratio Benefit, Participation of farmers, Claim Settlement, Diminishing Marginal Returns, PMFBY Scheme

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid advancement of digital technologies has significantly transformed creative industries, including textile design. Virtual Reality (VR) and Augmented Reality (AR) are emerging as powerful tools that enhance visualization, creativity, and experiential learning in textile design education and professional practice. These immersive technologies enable designers and students to simulate fabrics, patterns, textures, and garments in virtual environments, thereby reducing dependency on physical samples and traditional trial-and-error methods. The present study examines the role, applications, and impact of VR and AR in textile design education and industry practice. The research adopts a descriptive approach using primary and secondary data to analyze awareness, usability, and perceived benefits of VR and AR among textile students and professionals. The findings reveal that immersive technologies improve learning efficiency, creativity, cost-effectiveness, and sustainability in textile design processes. Despite challenges such as high initial investment and skill requirements, VR and AR have immense potential to redefine the future of textile design education and practice in the digital era.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Virtual Reality, Augmented Reality, Textile Design, Digital Education, Immersive Technology

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Social Realism, Vikram Seth, The Golden Gate, Hypermodernity, Alienation, Yuppie Culture, Indian Writing in English, Silicon Valley, Identity, Postmodernism, Loneliness.

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This paper examines India's evolving role in climate diplomacy within major international environmental agreements, including the UNFCCC, Kyoto Protocol, and Paris Agreement. It explores how India negotiates the tension between developmental priorities and increasing global expectations for climate mitigation. The study adopts a qualitative research approach based on secondary data, policy analysis, and academic literature. It argues that India's climate diplomacy has transitioned from a defensive, equity-based position to a more strategic and implementation-oriented approach. However, domestic political economy constraints--particularly coal dependence, energy demand, and financial limitations--continue to shape India's negotiation stance. The study further highlights that India's emphasis on climate justice and equity remains central to its diplomatic identity and contributes significantly to global climate governance debates. The paper concludes that India's effectiveness in future climate diplomacy will depend on its ability to align domestic implementation with international commitments while strengthening its leadership through institutional and coalition-based initiatives.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Climate Diplomacy, India, UNFCCC, Paris Agreement, Climate Justice, CBDR, Energy Transition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the linguistically diverse areas, access to basic healthcare information is scarce as it is affected by language barriers, delayed medical care, and unavailable digital support tools. This paper presents a multilingual healthcare assistant for preliminary symptom guidance, emergency severity assessment, and nearby hospital discovery across Indian languages. The system combines a web-based interface with machine learning models and rule-based reasoning to provide reliable and safety-aware answers. It has various Indian languages that allow interaction with users of different backgrounds. The architecture is a React based frontend with Fast API based backend, which guarantees scalable and real-time performance. Experimental evaluation demonstrated 90% symptom classification accuracy, 0.88 macro F1-score, and end-to-end response latency below 320 ms. It is a non-diagnostic design system and is focused on emergency escalation during the high-risk situations. Findings suggest that with the use of multilingual AI-based assistants in healthcare, preliminary healthcare support can be substantially more accessible and responsive.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Multilingual Healthcare, Symptom Analysis, Emergency Severity Classification, Machine Learning, Conversational Systems, Healthcare Accessibility

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

MilkRoute is a browser-based Progressive Web Application designed to digitize milk collection and payment workflows for rural dairy operations. It enables field agents to record milk entries with quality parameters (FAT, SNF, volume), automate grading, and process UPI-based payments in real time. The system supports multi-route collection, village tracking, and Bluetooth-enabled milk analyzer integration for accurate data capture. It also provides analytics dashboards for monitoring collection trends, payments, and quality distribution. Built using HTML, CSS, and JavaScript, MilkRoute operates fully on the client side, making it suitable for low-connectivity environments. The solution offers a scalable, cost-effective approach to modernizing last-mile dairy management.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: MilkRoute, Milk Collection Management, Rural Dairy Cooperative, Progressive Web App, UPI Payment, Bluetooth Milk Analyzer, FAT/SNF Quality Analysis, Route Management, Village Visit Workflow, Digital Payment, Collection Analytics, Offline-First Web Application.

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Creative Commons Attribution 4.0 and The Open Definition

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The meaning of 'women empowerment' is to establish women's rights which are nothing but human rights. It is clear by the speech of Hillary Clinton, the first lady of the United States at that time, at the fourth world conference on women in year 1995.These rights are- right to live respectfully, right to choose or make choices, right to take decisions about their own life, right to speak, freedom of movement and so on, are crucial for giving rise the sense of self-worth, self- confidence and self-respect in women. In India, as a consequence of many prevailing socio-cultural norms, these rights are neglected. Slow-paced social changes although lower down the intensity of negligence nevertheless, male-child preference in most of the Indian states tells us the story of women's rights abuses.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Women's rights, Male -child preference

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Creative Commons Attribution 4.0 and The Open Definition