Volume 14 | Issue 4 |

 Abstract

The increasing demand for engaging and accessible digital learning content has highlighted the limitations of traditional text-based educational materials. This paper presents an AI-based system that automatically converts educational text documents into segmented visual narration videos using a fully automated multimodal pipeline. The proposed framework integrates document parsing, Natural Language Processing (NLP), Large Language Models (LLMs), Text- to-Speech (TTS), and diffusion-based Text-to-Image (TTI) generation to transform static documents into structured, narrated video modules. Educational content is processed at the sentence level to enable fine-grained synchronization between narration, visuals, and subtitles. A robust primary-fallback strategy is employed across LLM, TTS, and image generation modules to ensure reliable operation. Experimental evaluation demonstrates that the system produces coherent and pedagogically suitable educational videos while significantly reducing manual effort and content production time through full pipeline automation. The proposed solution is scalable, cost-efficient, and well-suited for e-learning platforms, educators, and inclusive digital education delivery.

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 Keywords

Artificial Intelligence, Natural Language Processing, Generative AI, Text-to-Speech, Text-to-Image, Educational Content Automation, Visual Narration, Multimodal Learning, E-Learning Systems

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Creative Commons Attribution 4.0 and The Open Definition

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Turn-taking is a fundamental aspect of human communication that enables smooth and natural interaction. As conversational AI systems become more widely used in applications such as virtual assistants and real-time voice inter- faces, replicating this behavior has become a critical challenge. This paper explores how turn-taking mechanisms influence the perceived naturalness of human-AI conversations. It examines the underlying components that enable turn-taking, including speech detection, endpointing, and response timing, and analyzes the trade-offs between responsiveness and accuracy in real- time systems. The study highlights key challenges such as interruptions, variability in human speech, and environmental noise, which complicate reliable turn management. It further discusses modern design approaches, including adaptive models, predictive techniques, and user-control strategies, that aim to improve conversational flow. The findings suggest that effective turn-taking is essential for creating intuitive and engaging AI systems, and that no single approach fully resolves the inherent trade-offs.

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 Keywords

Turn-taking, Conversational AI, Real-time in- teraction, Speech systems, Human-AI communication

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This study examines the role of capital structure in determining firm performance and its impact on financial outcomes. The research focuses on how the mix of debt and equity influences profitability, risk, and overall firm value. Primary data were collected from 250 respondents using a structured questionnaire. The study adopts a descriptive and analytical research design and applies statistical tools such as percentage analysis, mean score analysis, and reliability tests. The findings reveal that factors such as financial risk, profitability, and optimal capital structure significantly influence firm performance. It is also observed that excessive debt increases financial risk, while a balanced capital structure enhances firm value and stability. The study highlights the importance of effective financial decision-making in achieving sustainable growth. Overall, the research provides valuable insights for managers, investors, and policymakers in optimizing capital structure for improved firm performance.

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 Keywords

Capital Structure, Firm Performance, Financial Risk, Profitability, Debt-Equity Ratio

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ABSTRACT RESEARCH STATEMENT: A study to assess the effectiveness of structured teaching program on knowledge regarding acid peptic disease and its prevention among the residents of selected community areas in Bangalore. BACK GROUND OF THE STUDY: Peptic ulcer disease (PUD) affects millions globally, with approximately 25 million Americans experiencing an ulcer in their lifetime. Once believed to be caused by stress and diet, up to 90% of ulcers are now attributed to Helicobacter pylori infection, a condition treatable with antibiotics. However, lack of awareness among patients and inconsistent treatment practices persist. PUD contributes to significant healthcare burdens, including hospitalizations, deaths, and economic costs. Additionally, unhealthy lifestyles and eating disorders, especially among adolescents, increase gastrointestinal risks. This study aims to raise awareness about PUD, promote early detection, and encourage healthier lifestyle choices to prevent complications. OBJECTIVES: 1. To assess the pre interventional knowledge of residents of selected community areas regarding the healthy lifestyle in preventing Acid peptic diseases 2. To assess the effectiveness of structured teaching programme on prevention of peptic ulcer among residents of selected community areas. 3. To find out the association between post interventional knowledge score of residents of selected community areas regarding the healthy lifestyle in preventing Acid peptic diseases and with their selected demographic variables. RESEARCH METHODOLOGY: The present study adopts a descriptive research design to assess the knowledge and awareness regarding peptic ulcer disease and its prevention. The target population includes individuals aged 20-60 years from selected urban and rural communities. A convenient sampling technique will be employed to select 100 participants. Data will be collected using a structured questionnaire, which includes both closed and open-ended questions related to symptoms, causes, risk factors (such as Helicobacter pylori infection and NSAID use), lifestyle practices, and preventive measures. The questionnaire will be validated by experts in gastroenterology and nursing. Prior informed consent will be obtained from all participants. Data will be analyzed using descriptive statistics (frequency, percentage, mean, and standard deviation) to determine the level of awareness, and inferential statistics (chi-square test) will be used to find associations between selected demographic variables and knowledge levels. Ethical approval will be obtained from the concerned institutional ethics committee before conducting the study. RESULT: The study assessed the effectiveness of a structured teaching programme on knowledge regarding acid peptic disease and its prevention among 60 residents of selected community areas in Bengaluru. Pre-test and post-test data were collected using a structured interview schedule. The analysis revealed a significant increase in post-test knowledge scores, indicating that the structured teaching programme was effective. The 't' test showed a statistically significant difference between pre- and post-test scores (p < 0.05). Chi-square test demonstrated a significant association between post-test knowledge and selected demographic variables such as education and source of information. Thus, the intervention proved beneficial in enhancing awareness. CONCLUSION: The study concluded that a structured teaching programme is effective in enhancing knowledge about acid peptic disease and its prevention. Educating the community through systematic health education can promote healthy lifestyle practices, reduce disease risk, and improve public health outcomes, especially in resource-limited community settings. Keyword:- Structured Teaching Programme , Acid Peptic Disease, Community Health, Knowledge Assessment, Prevention, Health Education, Bengaluru. UNDER THE GUIDENCE: SUBMITTED BY: MRS. SHREEDEVI G C MR. GHANSHYAM SINGH ASST. PROFESSOR M.SC. NURSING DEPT. OF COMMUNITY HEALTH NSG. DEPT. OF COMMUNITY HEALTH NSG. RGUHS, BANGOLORE (KARNATAKA). RGUHS, BANGOLORE (KARNATAKA).

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Keyword:- Structured Teaching Programme , Acid Peptic Disease, Community Health, Knowledge Assessment, Prevention, Health Education, Bengaluru.

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Lung cancer is one of the most life-threatening diseases worldwide, where early detection plays a crucial role in improving survival rates. This study proposes an efficient lung cancer classification and prediction system using Convolutional Neural Network (CNN) deep learning techniques. The model utilizes CT scan images as input and applies preprocessing steps such as normalization, noise reduction, and segmentation to enhance image quality. The CNN architecture automatically extracts deep features through convolutional, pooling, and fully connected layers, enabling accurate classification of lung nodules into benign and malignant categories. The proposed approach aims to reduce human error and diagnostic time while improving prediction accuracy. Experimental results demonstrate that the CNN-based model achieves high performance in terms of accuracy, precision, recall, and F1-score, making it a reliable tool for computer-aided diagnosis in medical imaging systems.

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Lung Cancer, CNN, Deep Learning, CT- Scan, Classification, Prediction

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Creative Commons Attribution 4.0 and The Open Definition

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Research Abstract This study examines the impact of digital banking on the performance of SMEs in Karnataka, focusing on the extent of adoption, financial outcomes, and factors influencing effective usage. The findings reveal that digital banking adoption among SMEs has grown steadily, with nearly 61% of enterprises integrating services such as online payments, mobile banking, and digital credit access. SMEs using digital banking reported notable improvements in financial performance, including a 17-20% increase in revenue, a 15% reduction in operational costs, and faster loan approvals compared to non-users. The study further identifies trust, digital literacy, and technological readiness as key determinants of successful digital banking utilization, with strong positive correlations to usage levels and efficiency gains. Despite the benefits, gaps remain in awareness, infrastructure, and perceptions of security, suggesting the need for improved digital literacy initiatives and stronger system safeguards. Overall, the research concludes that digital banking significantly enhances SME growth, financial transparency, and operational efficiency, making it a vital tool for strengthening the competitiveness and sustainability of SMEs in Karnataka.

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Keywords: Digital Banking, SME Performance, Adoption Factors

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Risk assessment and mitigation are most essential process to ensuring safety durability and performance of any structure, Residential structure are exposed to various types of risk including structural failures, construction defects, environmental issues and operational issues. This study focuses on identifying types of risk associated with residential building and evaluating their impact on safety, cost, time, environment and overall project performance. The process of risk assessment including identification of risk and analyzing and prioritization of risk based on their severity. This study also highlights practical mitigation measures such as proper design, use of good quality material, adherence to building codes, regular maintenance, and good site, supervision. Environmental consideration such as floods, earthquakes and soil conditions are also addressed to enhance resilience. A greater knowledge is anticipated to lead to more effective risk management and as result is a better project outcome and value for both contactors and clients. This study focused on importance of proactive planning and monitoring or supervision to reduce risks and ensure safe, economical and sustainable residential construction.

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Risk management, mitigation, environmental consideration, prioritization of risk, performance of residential structure, safety, building codes

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Creative Commons Attribution 4.0 and The Open Definition

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Parkinson's disease is a chronic progressive neurodegenerative disorder characterized by tremor, rigidity, bradykinesia, and postural instability. This review aims to integrate Unani and modern perspectives of Parkinson's disease. A literature-based review was conducted using classical Unani texts and standard modern medical references. Modern medicine attributes Parkinson's disease to degeneration of dopaminergic neurons in the substantia nigra leading to dopamine deficiency and imbalance with acetylcholine. In Unani medicine, similar conditions are described under Ra'sha and Istirkha, associated with Su-e-Mizaj Barid and dominance of Balgham. An integrative approach combining both systems may improve patient outcomes.

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Parkinson's disease, Ra'sha, Unani medicine, Neurodegeneration, Dopamine deficiency,integrative medicine.

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Creative Commons Attribution 4.0 and The Open Definition

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Modern search engines handle billions of queries daily, requiring extremely fast and scalable data structures. Traditional indexing methods such as B-trees and inverted indexes face limitations in latency and memory efficiency at large scale. To address this, hybrid approaches combining prefix-based and hash-based techniques are explored to achieve faster query processing and better resource utilization.

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Trie Hash Table Hybrid Trie-Hash Architecture (HTH) Search Engine Optimization Prefix Search Autocomplete Systems Cuckoo Hashing Robin Hood Hashing Consistent Hashing Distributed Indexing Information Retrieval

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The construction industry is increasingly focusing on sustainable and eco-friendly materials to reduce environmental impact and enhance resource efficiency. Natural fibres have gained significant attention as reinforcement materials in concrete due to their low cost, renewability, and biodegradability. This study investigates the effect of incorporating water hyacinth fibre as a natural reinforcement on the fresh and hardened properties of concrete. The fibres extracted from water hyacinth were subjected to alkali treatment using sodium hydroxide (NaOH) solution to improve fibre-matrix bonding. Concrete mixes were prepared with varying fibre contents and tested for workability, compressive strength, split tensile strength, and flexural strength. The results indicate that fibre inclusion enhances tensile and flexural properties due to crack-bridging mechanisms, while workability decreases with increased fibre content. The study demonstrates that water hyacinth fibre can be effectively utilized as a sustainable reinforcement material, contributing to waste utilization and improved performance of concrete.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Water Hyacinth Fibre, Alkali Treatment, Compressive Strength, Split Tensile Strength, Flexural Strength

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Creative Commons Attribution 4.0 and The Open Definition