Volume 14 | Issue 3 |

 Abstract

This paper explores the concerted relationship between Lucknow's rich culinary heritage and its representation in Indian cinema. The city's iconic cuisine, characterized by kababs, biryani, and sheermal, has been a recurring theme in Bollywood films, showcasing its cultural significance and allure. Films like 'Tanu Weds Manu' and 'Ishaqzaade' have not only highlighted Lucknow's architectural and picturesque settings but also its delectable food, introducing the city's culinary identity to the world. This study examines how cinema has contributed to the popularization of Lucknow's cuisine, promoting a cross cultural understanding and appreciation. Through a critical analysis of film narratives and culinary traditions, this research paper is an attempt towards highlighting the intersection of food and cinema which has played a significant role in shaping Lucknow's cultural narrative, making its cuisine an integral part of India's gastronomic and cinematic landscape.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Lucknow, cuisine, cinema, Bollywood, gastronomy

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The secure storage of user credentials is a critical requirement for modern authentication systems. This project focuses on analyzing and implementing Argon2id, the recommended variant of the Password Hashing Competition winner, to evaluate its efficacy in secure password storage. Argon2id provides robust resistance against brute-force and GPU-based cracking attacks through its configurable parameters, specifically time cost, memory cost, and parallelism. The main goal of this research is to evaluate how parameter tuning affects both performance and security in real-world environments and to perform a systematic comparative evaluation of Argon2id and established password hashing algorithms such as bcrypt, scrypt, and PBKDF2. To accomplish this, a prototype login and registration system was implemented using Python and Flask, incorporating an automated benchmarking module to measure execution time and memory usage, and overall efficiency. The comparative analysis and performance benchmarking highlight the trade-offs between usability and security under varying configurations. The results demonstrate that Argon2id effectively balances speed and memory hardness, providing strong resistance against brute-force attacks while maintaining practical authentication latencies. Ultimately, this paper provides practical recommendations and guidelines for developers to adopt secure parameter choices in CPU-based web environments while considering real-world system constraints.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Argon2id, Password Hashing, Parameter Optimization, Memory-Hard Functions, Authentication Systems, Performance Benchmarking.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Ocean pollution has become a serious environmental issue that threatens marine ecosystems, biodiversity, and human health. Traditional monitoring approaches, such as ship-based surveys and manual interpretation of satellite imagery, are costly, time-consuming, and limited in spatial coverage. To overcome these limitations, this paper presents an automated ocean pollution detection system using satellite imagery analysis and deep learning-based computer vision techniques. The proposed framework utilizes the You Only Look Once (YOLO) object detection model to identify and localize major surface-level pollutants, including oil spills, harmful algal blooms, and floating plastic waste. Prior to detection, satellite images are pre-processed using OpenCV to enhance image quality and ensure compatibility with the detection model. The trained YOLO model is integrated into a Flask-based web application that enables users to upload satellite images and visualize detection results in real time. The system highlights polluted regions using bounding boxes and provides confidence scores for each detection. Experimental evaluation demonstrates that the proposed approach achieves reliable detection performance with fast inference speed, making it suitable for practical environmental monitoring applications. The modular architecture of the system supports scalability and cloud deployment for large-scale ocean surveillance. The results indicate that combining satellite remote sensing with deep learning offers an efficient and cost-effective solution for automated marine pollution monitoring.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ocean Pollution Detection, Satellite Imagery, Computer Vision, YOLO, Deep Learning, Remote Sensing, Environmental Monitoring.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Modern digital ecosystems demand software systems that sustain high performance, reliability, and maintainability as user bases and data volumes grow exponentially. This paper investigates the design and development of a scalable software solution capable of adapting to evolving workloads without compromising service quality. The study synthesizes established architectural principles, distributed-systems theory, and contemporary engineering practices to propose an integrated five-layer framework spanning presentation, application logic, data management, infrastructure, and observability. A mixed-methods research design combines systematic literature analysis with prototype-based experimentation on a cloud-hosted microservices platform. Experimental results demonstrate that the proposed architecture achieves near-linear horizontal scalability up to thirty-two nodes, with a mean response-time increase of less than twelve percent across a tenfold traffic surge. Key findings affirm that scalability is an emergent property arising from coherent architectural decisions, polyglot data persistence, automated infrastructure provisioning, and robust observability pipelines rather than any single technology choice. The paper concludes with practical engineering guidelines and directions for future research in autonomous, self-healing scalable architectures.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

scalable architecture, microservices, distributed systems, cloud computing, Kubernetes, horizontal scaling, fault tolerance, DevOps, CI/CD, container orchestration, event-driven architecture, polyglot persistence, API gateway, observability, autoscaling, performance engineering, CAP theorem, system reliability, load balancing, resilience.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Literature, in both its poetic and dramatic forms, constitutes one of the most prominent cultural tools in shaping societal consciousness and guiding it towards the values of civilization and progress, particularly during periods of transformation and crisis. This research examines and analyses the role played by British literary production in the post-World War II and post-colonial eras in shaping the intellectual and social structure of British society. This is achieved through a critical reading of several poetic and dramatic works that reflected profound transformations in identity, belonging, power, and social justice. The research focuses on how poetry contributed to framing collective consciousness in relation to crises and human experiences, while theatre contributed to exposing oppressive structures and questioning cultural and political systems. The research adopts an analytical-cultural approach that connects literary texts to their historical and social contexts. It seeks to demonstrate how British literature, through its aesthetic and intellectual tools, contributed to supporting the path of civilizational transformation and establishing a humanistic and resistant discourse based on the values of dialogue, accountability, and renewal. This study confirms that literature is not merely a mirror of reality, but a key player in reshaping it.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

British literature, cultural transformation, British poetry, British theatre, post-crisis, cultural consciousness

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research project presents the design and implementation of a smoke detection system utilizing Internet of Things (IoT) technology to mitigate the risks of fire accidents, which often lead to significant property loss and fatalities. The primary objective is to develop an interconnected safety system that can identify smoke and hazardous gases without human intervention. The system's methodology centers on a prototype developed within the Tinkercad simulation environment. The core hardware consists of an Arduino UNO R3 microcontroller and an MQ-2 metal oxide semiconductor (MOS) sensor. The MQ-2 sensor is chosen for its ability to detect flammable gas concentrations between 300 and 10,000 ppm, including smoke, LPG, propylene, and hydrogen. Additional components include a piezo buzzer for audible alerts, red and green LEDs for visual status indicators, and an LCD screen for real-time messaging. The system functions by monitoring voltage fluctuations from the MQ-2 sensor, which are proportional to smoke concentrations in the environment. Through an if-else control loop, the system compares live sensor data against a predefined threshold of 400. Results from testing demonstrate that when smoke levels exceed this threshold, the system successfully triggers a red LED and a continuous buzzing alarm, while maintaining a green LED status during safe conditions. The proposed system offers a portable and efficient solution for early fire detection, with future work recommended to improve sensitivity for low-energy flames and further minimize false alarms.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT, Smoke Detection, Arduino UNO, MQ-2 Sensor, Fire Safety, Embedded Systems

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Floral waste generated from temples, religious activities, weddings, and social functions forms a considerable portion of biodegradable waste in India. Due to cultural and religious beliefs, flowers offered during rituals are often disposed of in rivers, ponds, or open areas rather than through organized waste management systems. Such practices contribute to environmental problems including water pollution, foul odour, soil contamination, and emission of greenhouse gases during decomposition. Although floral waste is biodegradable, its slow degradation rate and improper handling make it an environmental concern. At the same time, discarded flowers contain valuable natural components such as pigments, organic matter, and aromatic compounds, which remain largely underutilized.The present study focuses on the utilization of floral waste for the preparation of eco-friendly value-added products, supporting the concept of a circular economy. Floral waste was collected from nearby temples, manually segregated, and processed using simple, low-cost, and environmentally safe methods. Various products such as natural pigments, Holi colours, herbal lip balm, incense (dhoop), cloth tags, seeded paper, handmade paper, diary, and compost were prepared from discarded flowers. The prepared products were qualitatively evaluated based on colour, texture, fragrance, and usability. The findings indicate that floral waste can be effectively reused as a useful bio-resource instead of being treated as waste. This approach not only reduces environmental pollution but also promotes resource recovery, waste minimization, and sustainable waste management practices. The study highlights the potential of small-scale floral waste utilization as a practical step towards circular economy and environmental sustainability.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Floral waste Value-added products Circular economy Sustainable waste management Eco-friendly materials Resource recovery

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: Proper evaluation of pulp vitality is essential for accurate diagnosis and effective endodontic treatment planning. Dental students and interns must have sufficient knowledge and awareness of pulp vitality testing methods to ensure appropriate clinical decisions. Aim: To evaluate the knowledge, attitude, and awareness related to pulp vitality tests among dental students and interns. Materials and Methods: A cross-sectional survey was carried out among 262 dental students and interns, including third-year students, final-year students, and interns. A structured questionnaire consisting of demographic information and 15 multiple-choice questions was used to assess knowledge of pulp vitality tests. Each correct response was given a score of 1, and incorrect responses were scored as 0, with a maximum possible score of 15. Descriptive statistics were used to summarize the data, and a one-way Analysis of Variance (ANOVA) test was applied to compare knowledge scores among the three groups. A p-value of less than 0.05 was considered statistically significant. Results: The overall findings indicated moderate to good knowledge among participants. Final-year students showed slightly higher average knowledge scores compared to third-year students and interns. However, the difference between the groups was not statistically significant (F = 1.71, p = 0.183). Conclusion: The study demonstrated that dental students and interns possess an acceptable level of knowledge regarding pulp vitality tests, with no significant variation among the academic groups. Continued clinical training and educational programs are recommended to improve awareness and practical skills.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pulp vitality test, Dental students, Interns, Knowledge, Awareness, Attitude

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Second-generation immigrant literature increasingly portrays identity not as an automatic inheritance but as something produced through continual negotiation between memory, culture, and everyday experience. This study investigates hybrid identity in On Earth We're Briefly Gorgeous by Ocean Vuong and White Teeth by Zadie Smith, focusing on how migrants' children shape their sense of self within spaces shaped both by family histories and contemporary national life. Whereas first-generation narratives usually emphasize movement and adaptation, second-generation works address inherited displacement -- a condition in which people feel cultural tension despite being born in the receiving society. Identity therefore develops not from migration itself but from its psychological and cultural consequences.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Second-generation immigrant literature increasingly portrays identity not as an automatic inheritance but as something produced through continual negotiation between memory, culture, and everyday experience.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Social media platforms generate massive volumes of data every second, making it difficult for individuals and organizations to manually analyze public opinion and engagement trends. Twitter (X), being one of the most influential microblogging platforms, plays a major role in shaping public sentiment, brand perception, and digital communication. This project presents an AI-Driven Twitter Analytics Dashboard built using Python, Streamlit, Plotly, and Natural Language Processing (NLP) techniques. The system analyzes Twitter posts and provides real-time insights into user engagement and public sentiment. It processes tweet data and extracts key performance metrics such as likes, retweets, replies, views, and engagement rate. Using TextBlob sentiment analysis, the application automatically classifies tweets into positive, neutral, and negative categories. The dashboard visualizes results through interactive graphs including sentiment distribution, engagement histograms, and performance comparison charts. The platform also supports data export in CSV and Excel formats, enabling further offline analysis. This project demonstrates how artificial intelligence and data visualization can be combined to create an intelligent, user-friendly analytics tool for social media monitoring, brand tracking, and trend analysis

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI-Driven Analytics, Twitter Analytics Dashboard, Sentiment Analysis, Natural Language Processing, Data Visualization, User Engagement Metrics, Social Media Monitoring

  License

Creative Commons Attribution 4.0 and The Open Definition