Communities in DSpace
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FINITE VOLUME METHOD FOR SOLVING NAVIER STOKES EQUATIONS IN FLUID DYNAMICS
(An-Najah National University, 2025-06-24) Abu Arrah, Abdulraheem
Several equations, particularly the Navier-Stokes equations, govern fluid dynamics. These
equations are essential for describing fluid motion, which helps us understand many natural
phenomena. The Navier-Stokes equations present significant challenges for researchers in
mathematics and engineering due to their complexity and the difficulties in obtaining
analytical solutions. As a result, it has become necessary to explore alternative methods for
solving these equations, particularly through numerical approaches. Since numerical
methods yield approximate solutions, it is vital to evaluate the effectiveness of this
approach in addressing the Navier-Stokes equations.
One such numerical method is the finite volume method (FVM), which provides
approximate solutions to the Navier-Stokes equations. In this thesis, we conducted a
thorough examination of the finite volume method using various examples of the Navier Stokes equations that have analytical solutions. We began with simpler cases and gradually
increased the complexity while also comparing our numerical results with the analytical
solutions to assess how closely they aligned with the exact solutions. This comparison
enabled us to evaluate the effectiveness of the method.
We encountered issues related to the stability and accuracy of the numerical solutions based
on the specific conditions we examined while employing this method. As a result, we
discussed the numerical schemes related to the Finite Volume Method (FVM) and the
criteria for selecting a specific scheme, especially concerning the Peclet number. We then
evaluated the effectiveness of each scheme by applying them to the same case.
The results obtained from the finite volume method for solving one-dimensional steady state Navier-Stokes equations, with a suitable choice of discretization scheme, provided
accurate solutions with excellent stability. However, we observed that when high Peclet
numbers were used, solution instability emerged, necessitating the implementation of
higher-order discretization schemes.
Future research could build on this method by looking at flow situations in two or three
dimensions and improving computing efficiency with adaptive mesh refinement (AMR)
and better discretization schemes.
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Drill and Plow Machine
(2024) Sama Abosair, Fatima Zhraa Raeq Saidi; Fatima Zhraa Raeq Saidi
This project focuses on developing a robot designed to assist farmers in ploughing and digging
tasks, reducing the physical stress associated with manual labor, especially during extreme weather
conditions. The robot is equipped with a plough and a digging tool and is powered by lithiumion
batteries. It operates through an application that provides two basic modes of operation:
an autonomous ploughing mode where the robot ploughs the soil while avoiding obstacles, and a
ploughing and digging mode that allows the farmer to have full control over the robot’s movements.
The digging mode also allows for precise control of the digging operations. In addition, the robot
was tested in real field conditions, showing a significant reduction in the physical effort required
from farmers and an improvement in the efficiency of ploughing and digging.
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EliteStay
(2025) Fatima Zhraa Saidi; Lana Sammer Hassan
EliteStay is a modern electronic platform aimed at revolutionizing the hotel
reservation and exploration process while aiding in the advancement
and progress of the tourism industry in Palestine. This groundbreaking
platform enables users to effortlessly find and book lodging from the comfort
of their homes, using an easy-to-navigate mobile app that is available
to all.
EliteStay seeks to transform convenience through an easy-to-use interface
that enables customers to discover a variety of hotels, access comprehensive
descriptions, check amenities, compare rates, and complete
bookings with a few taps. The platform not only streamlines the planning
process but also enhances sustainability and encourages economic
development by highlighting local hospitality enterprises and backing the
domestic tourism sector.
Prioritizing accessibility and inclusivity, EliteStay guarantees that travelers
of diverse backgrounds can discover accommodations suited to their
preferences and financial capacities. Regardless of whether the trip is
for leisure, business, or family, the platform offers a tailo experience by
linking users to hotels that align with their preferences.
EliteStay serves as a crucial link between tourists and the local tourism
network, enhancing community connections, supporting local enterprises,
and highlighting the vibrant cultural heritage and distinct hospitality of
Palestine.
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Real Time Ransomware Detection and Mitigation Using Machine Learning
(2025-06-18) Bahaa Nofal
Abstract
Ransomware remains one of the most dangerous cybersecurity threats, causing severe damage by encrypting user data and demanding payment. Traditional antivirus systems often fail to detect new or evolving ransomware strains due to their reliance on signature-based detection. In this project, we present an intelligent, real-time ransomware detection and mitigation system that leverages behavioral analysis and machine learning. The system monitors file activities, registry operations, and network behavior using C++ and Windows APIs, and extracts technical features from executable files. These features are then classified using a trained Random Forest model in Python to determine whether a file is benign or malicious. If ransomware is detected, the system takes immediate action to stop the threat before it causes harm. The integration between C++ and Python enables efficient real-time classification, while the system’s modular design ensures extensibility and adaptability to new threats. Our solution was tested on real-world samples in a controlled virtual environment, and achieved high accuracy in detecting ransomware before execution.
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A PROPOSED METHOD FOR MITIGATION THE UNBALANCED CURRENTS IN POWER DISTRIBUTION NETWORK WITH PV SYSTEMS
(An-Najah National University, 2025-04-23) Raed Aref Kmail, Ahmad
This study aims to solve the problem of uneven electricity use in homes that share a three-phase power supply. This unevenness happens when too many houses rely heavily on just one or two of the three power lines, leading to wasted power, overloaded lines, voltage drops and even blackouts. The growing use of solar panels on homes makes this problem even worse since the amount of electricity they produce can fluctuate .
To fix this, the project created a smart system that uses a microcontroller and WiFi technology to constantly monitor and adjust how electricity is distributed among the three power lines. It keeps track of how much power each house uses and how much solar energy is being produced, then automatically shifts houses between the lines to keep things balanced.
Tests of this system show losses reduced from 138 kW to 9 kW—resulting in cost savings of $193.2, or $3.75 per house. The system achieved a simple payback period of less than one month. Furthermore, the lowest network voltage improved from 206 V under unbalanced conditions to 221 V after implementing the balancing solution.
This study is important because it shows how to better manage modern power grids that include a lot of solar energy. By using this system, power companies can ensure a more stable and dependable electricity supply to homes while also supporting the use of renewable energy sources like solar power.