The methods and procedures involved in this study encompassed a thorough analysis of existing inventory management practices and the design and development of a bespoke IMS. The system integrates real-time tracking, and data analytics to facilitate inventory control, demand forecasting, and procurement processes. Additionally, user-friendly interfaces were designed to enhance usability and accessibility across organizational levels.
]]> ]]> ]]> The application addresses the problem of limited access to personalized, diverse, and engaging story content, especially for children from various cultural and linguistic backgrounds. By integrating advanced AI services, the platform generates unique stories based on user-provided inputs such as title, age group, genre, and illustration style. Using technologies like Google AI, Hugging Face’s text generation models, and custom text-to-speech tools, the system delivers cohesive narratives paired with AI-generated visuals and narration. The backend is developed using Node.js and Express.js, while the frontend is built with React.js, offering a responsive and user-friendly interface. Data is securely stored and managed using a Drizzle ORM with a PostgreSQL database.
Results show that the system can produce high-quality storybooks with consistent plots, age-appropriate language, and stylized imagery, enhancing the reading experience. The platform also includes features like story exploration, user account management, coin-based generation limits, and payment integration for purchasing additional credits.
In conclusion, the AI Storybook Generator showcases the potential of merging generative AI with interactive design to promote literacy and creativity in young users. Future work may involve mobile app development, multilingual support, story sharing features, and integration of educational objectives into story structure. The application serves as a scalable, customizable tool for families, educators, and storytellers worldwide.
]]> ]]> The application addresses the problem of limited access to personalized, diverse, and engaging story content, especially for children from various cultural and linguistic backgrounds. By integrating advanced AI services, the platform generates unique stories based on user-provided inputs such as title, age group, genre, and illustration style. Using technologies like Google AI, Hugging Face’s text generation models, and custom text-to-speech tools, the system delivers cohesive narratives paired with AI-generated visuals and narration. The backend is developed using Node.js and Express.js, while the frontend is built with React.js, offering a responsive and user-friendly interface. Data is securely stored and managed using a Drizzle ORM with a PostgreSQL database.
Results show that the system can produce high-quality storybooks with consistent plots, age-appropriate language, and stylized imagery, enhancing the reading experience. The platform also includes features like story exploration, user account management, coin-based generation limits, and payment integration for purchasing additional credits.
In conclusion, the AI Storybook Generator showcases the potential of merging generative AI with interactive design to promote literacy and creativity in young users. Future work may involve mobile app development, multilingual support, story sharing features, and integration of educational objectives into story structure. The application serves as a scalable, customizable tool for families, educators, and storytellers worldwide.
]]> ]]> ]]> The problem addressed is the overloaded global freelance market, and the lack of opportunities for local freelancers and young talents to showcase their skills and knowledge.
Two important features set BalkanFreelance apart: a strong role-based authentication system guaranteeing platform security and trust, and a hybrid payment system enabling both conventional ways (PayPal) and blockchain-based transactions.
The platform's core functionality includes comprehensive gig management, so the users are able to create their own gigs as well as search for opportunities that match their skills.
While acknowledging challenges such as market competition and trust-building, BalkanFreelance aims to empower local professionals, create new income streams, and foster a digital community that supports self-employment.
This project shows how locally focused digital solutions could boost entrepreneurship and generate economic growth within the Balkan region's growing gig economy.
]]> The development process was divided into several key phases: planning, design, implementation, and testing. The frontend of the application was built using standard web technologies such as HTML, CSS, and JavaScript to ensure responsiveness and clarity in design. On the back-end, PHP and MySQL were used to handle database interactions and user inputs, ensuring the dynamic functionality of the site. The initial phase involved a thorough analysis of user and business requirements, followed by the design of an efficient database structure to support product listings and user data. The completed application went through multiple testing iterations aimed at improving performance and optimizing usability.
The final outcome of the project was a fully functional, user-oriented web application that allows smooth interaction with the content. By centralizing the display of all available jewelry items, the platform helps maintain consistent data management while reducing operational costs and time. Moreover, the resulting digital storefront positions Blingho to enter broader markets with a polished and professional online image. Overall, the techniques and tools employed during the development proved effective in achieving the project’s objectives. Looking ahead, further enhancements could include the addition of advanced features and strengthened security protocols to support future scalability and user trust.
]]> ]]> BNDMS is implemented as a Django-based monolith with two logical layers (api and front_end). A custom Account model provides role-based access control (levels: logged-in user, emergency worker, organizer, admin). Core domain models – Report, Task, News, and Request – inherit from a shared base with UUID identifiers and soft-delete for auditability. Methods and procedures include: server-rendered forms for validation and CSRF protection; a thin controller layer that encapsulates uniform CRUD operations and soft-delete semantics; Bootstrap-based templates for a responsive UI; and a geospatial workflow where user-submitted addresses are geocoded and stored as latitude/longitude for immediate display on a Leaflet map with OpenStreetMap tiles. End-to-end procedures cover account registration and login, incident reporting (title, description, address → coordinates), organizer assignment of tasks to specific users, emergency-worker status updates, and the publication of official news by privileged roles. Quality is supported by unit tests for models, Selenium scaffolding for system flows, and management commands for repeatable role administration.

Results show a working system that enables citizen reporting, real-time map visualization from stored coordinates, structured tasking tied to incidents, and transparent publication of official information – while preserving history and enforcing permissions. The conclusion is that BNDMS delivers a maintainable, open, and extensible foundation for operational situational awareness in a disaster context and is well positioned for future enhancements such as a REST API, PostgreSQL/PostGIS, richer spatial analytics (e.g., clustering and proximity queries), and a mobile client.
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In the increasingly competitive higher education landscape, digital marketing plays a crucial role in attracting prospective students. However, institutions often face major challenges in tracking cross-channel performance and accurately attributing student applications to specific campaigns. Marketing platforms like Meta Ads and Google Ads often exaggerate campaign effectiveness by counting impressions, clicks, and superficial conversions that may not result in actual applications or enrollments.
This senior design project addresses that issue by developing a Business Intelligence Platform for PPC and Organic Marketing, aimed at providing real-time, actionable insights for the International Burch University (IBU) Marketing Team. The system enables end-to-end campaign tracking by integrating digital ad performance data with actual application data, using a unique medium URL parameter embedded in campaign links and captured during the application process to bridge external and internal data sources.
The platform uses Windsor.ai connectors to fetch ad data into Google Sheets, where a Google Apps Script automates data cleaning and merging. This data is combined with student application records from a MySQL database and visualized in real-time through Looker Studio dashboards.
Results demonstrate the system’s ability to provide clear, actionable insights, enabling the marketing team to compare channels, calculate cost per application, and evaluate the full applicant funnel across departments and academic cycles. In doing so, the platform empowers the team to optimize campaigns based on verified outcomes.
The project highlights the importance of reliable tracking infrastructure, disciplined use of URL parameters, and automation in marketing analytics. It represents a scalable, low-cost solution for improving data-driven decision-making in higher education marketing.
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