Computer Engineering / Software
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- ItemHealthcare Management & Shopping System (HMSS)(2026) Mohammad Badawi; Ammar Mohammad AmmaThis project presents HMSS (Healthcare Management & Shopping System), a comprehensive and integrated digital platform developed for beauty centers, healthcare clinics, and educational academies. The system is built as a cross-platform solution with a React-based web frontend, a React Native (Expo) mobile application for iOS and Android, and a Django REST Framework backend with a MySQL database. HMSS adopts a role-based access control system supporting six user types: Admin, Secretary, Customer, Student, Worker (Specialist), and Teacher, each with tailored dashboards and permissions. The platform consolidates clinic operations, e-commerce, appointment booking, course management, payroll and HR, and a loyalty rewards system into a single unified ecosystem. Customers interact with a modern, responsive interface to browse products, book appointments through a multi-step wizard, enroll in courses, and manage orders. The e-commerce module supports product variants, attributes, categories, wishlist, cart, checkout with cash-on-delivery, and return/refund requests. The booking system offers real-time scheduling with worker availability tracking and supports both regular services and multi-session therapy treatments. Administrators and secretaries manage offices, sections, products, appointments, courses, complaints, and finances through dedicated dashboards. The system includes a full accounting module with income/outcome tracking, a notification system (in-app and SMS), and an AI-powered chat assistant that answers user queries about products, services, and courses. The web version provides optimized interfaces for desktop screens with data tables, advanced filtering, and comprehensive management tools. The mobile application mirrors the customer-facing features with a native experience including push notifications, theme customization (Light, Dark, and Luxury), multi-currency support, and bilingual content (Arabic RTL and English LTR). With its rich feature set — including intelligent appointment booking, e-commerce with variants, educational course management, loyalty points, AI-driven assistance, and secure role-based
- ItemDevForce(2025) Rasheed Hendawi; Mohammad AbuRehanThe goal of this graduation project is to design and implement a web-based platform for competitive programming, inspired by the widely-used Codeforces website. This platform will offer users the ability to participate in algorithmic problem-solving contests, submit code in multiple programming languages, receive instant feedback via a judging system, and engage with a community of developers through rankings, discussions, and virtual contests. The core functionality will include user registration and authentication, contest creation and management, problem submissions with automated judging, leaderboards, and user profiles. A responsive, modern user interface will be developed to ensure a seamless experience across both web and mobile devices. To achieve this, the project will utilize React for building a dynamic and interactive frontend, while ASP.NET Core will serve as the backend framework to handle API endpoints, authentication, and business logic. In order to extend the platform's reach to mobile users, a dedicated mobile application will be developed using React Native, ensuring a consistent user experience across Android and iOS. The system’s architecture will follow a micro services pattern where suitable, and all services will be containerized using Docker to ensure portability, scalability, and ease of deployment. Additional technologies such as PostgreSQL (or another relational database), Redis (for caching and queue management), and Nginx (as a reverse proxy and load balancer) may also be integrated as part of the infrastructure. This project aims not only to replicate essential features of platforms like Codeforces, but also to introduce enhancements in usability, user engagement, and educational tools for learners. By the end of the development cycle, CodeChallenge will represent a fully functional, scalable, and extensible system for online programming competitions and skill-building.
- ItemENHANCING RESOURCE UTILIZATION IN EDGE COMPUTING USING DEEP Q-NETWORK(جامعة النجاح الوطنية, 2026-01-18) Yazan JarrarThis thesis focuses on designing and evaluating machine learning techniques to enhance the scheduling process in an edge computing environment, especially for IoT applications, with the goal of maximizing the number of tasks executed within a specified window limit. Maximizing task completion within deadlines increases throughput and service quality, while missed deadlines can degrade system performance and render results unusable. This study investigates the two proposed algorithms, Simulated Annealing (SA) and Deep Q Network (DQN), to determine if they outperform the existing solutions for batch task scheduling in an edge computing environment. To validate the results, we used real world Augmented Reality (AR) and Internet of Vehicles data generated by the EdgeCloudSim simulator. The results clearly show that our proposed algorithms outperform others solutions, especially where the resources are strictly constrained. The results show that our simulated annealing-based algorithm achieved up to a 71% reduction in task failure rate compared with the baseline algorithm when tested in static environments using real IoT and AR data. They also show that our Deep Q-Network based scheduler consistently achieved the lowest failure rates across dynamic scenarios, especially under higher constraints. Moreover, the Deep Q-Network model evaluated in a dynamic environment required substantially less overhead time, under one-third of the simulated annealing algorithm’s runtime, while both algorithms outperformed other baseline algorithms by up to 10% in task failure rate. These findings support the thesis objective of maximizing the edge resource utilization while ensuring task batches complete within a specified window limit and highlight the efficiency of the Deep Q-Network based scheduling algorithm.
- ItemAn-Najah National University Faculty of Engineering & Information Technology Computer Engineering Department Presented in partial fulfillment of the requirements for Bachelor degree in Computer Engineering 2025 Graduation Project 1 - Software PalHands(2025) Abeer Kharouf; Rand JohariThis project presents a mobile and web application designed to facilitate the process of offering and requesting services. Service providers can showcase the services they offer, while users can search for the desired service and select a suitable provider based on ratings and reviews from previous clients. The platform integrates an interactive map powered by GPS, enabling users to easily identify and choose the nearest provider. The system also allows users to view the provider’s availability schedule, book an appointment at a suitable time, and await confirmation. Notifications are sent to providers when a booking request is made, allowing them to review the requester’s details as well as feedback and ratings from other providers who previously worked with that user. Once a booking is either accepted or rejected, the user is promptly notified. Cancellations are supported under specific conditions: a request can be withdrawn freely if made at least two days prior to the appointment, whereas cancellations within two days require approval from the other party. After completing a service, both users and providers can submit reports or complaints about each other, ensuring accountability. Additionally, the platform supports suggestions for new services, which are reviewed by the administrator before approval to prevent misuse. For security and reliability, administrators have the authority to suspend or remove any user or provider account, along with all associated bookings, while notifying the relevant parties. Direct communication between providers and users is supported, as well as access to frequently asked questions and AI-powered assistance to guide users through the platform. Furthermore, providers can specify availability for emergency services, such as late-night or weekend requests, which can be booked at least two hours in advance. Overall, this system enhances service accessibility, reliability, and efficiency by connecting users with trusted providers in a secure and user-friendly environment.
- ItemDentify - A Comprehensive Dental Clinic Management System(2026) Ala’a Abdelrahim; Abdullah ShabibModern dental practices face significant operational challenges including inefficient ap- pointment management, fragmented patient records, and limited patient engagement. This project addresses these challenges through the design, development, and implementation of Dentify—a comprehensive, cloud-based dental clinic management system integrating web and mobile applications to streamline dental practice operations and enhance patient care delivery. The system was developed using a three-tier architecture with Node.js and Express for RESTful API implementation, PostgreSQL with Prisma ORM for data management, and Fire- base Firestore for real-time communications. The frontend comprises responsive web appli- cations built with React.js for patients, dentists, clinic administrators, secretaries, radiology centers and system administrators, complemented by cross-platform mobile applications devel- oped using React Native for patients, dentists and secretaries. A key innovation is the integration of Google Gemini 2.5 Flash AI to power an intelligent chatbot providing patient support and appointment booking through natural language interaction. Security measures include HTTPS encryption, bcrypt password hashing, JWT authentication, and role-based access control sup- porting six distinct user types. The implemented system successfully delivers nine core modules: authentication and user management, intelligent appointment scheduling with real-time availability, comprehensive treatment planning with visual dental charting, flexible payment processing, radiology inte- gration, AI-powered chatbot assistance, clinic management, administrative oversight, and real- time notifications. The system demonstrates significant advantages over traditional solutions through modern user interfaces, AI-enhanced patient engagement, integrated clinical and ad- ministrative workflows, real-time data synchronization, and cost-effective deployment using open-source technologies. The project validates that contemporary web technologies, cloud platforms, and artificial intelligence can effectively address complex healthcare management requirements while improving user experience and reducing costs compared to legacy commer- cial solutions