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Recent Submissions
Quality assessment of ChatGPT and Gemini English into Arabic translation in the domain of climate change : A comparative study /
El-Outify, Yara Tarek,; Supervisor : Mustafa Riad, Maha Fathi, Hanan Sharaf El-Dine. Includes Arabic Summary.
Fracture resistance of zirconia versus PEEK implant supported cantilever fixed partial denture with two span Lengths : (An in vitro study) /
Shedid, Roshan Mohamed Tarek,; Supervisor : Hesham Katamish, Rana Sherif. Includes Arabic Summary.
New methods for the selective determination of active pharmaceutical ingredients /
Saber, Yomna Ayman,; Suoervisor : Samy El- Sayed Sayed Ahmed Emara, Fotouh Mansour, Noha Ibrahim. Includes Ararbic and English Summary.
Digital radiographic assessment of the shaping ability of A contemporary rotary system in curved root canals using two different torque settings /
Helmy, Omar Mohamed Nader Hassan,; Supervisor : Nihal Ezzat Sabet, Mohamed Nabeel. Includes Arabic Summary.
Conventional versus digital measurements of marginal and internal fit of milled interim restorations :| (An In-Vitro study) /
El Attawy, Ahmed Mohamed,; Supervisor : Tamer Elhamy Shokry, Yara Sayed. Includes Arabic Summary.
Design, synthesis and biological evaluation of novel thiazolidinone derivatives as anti-cancer agents : (In vitro study) /
Kenawy, Omnia Gamal Mubarak,; Supervisor : Nahla Ahmed Hassan Farag, Khaled Omar Ahmed Mohamed, Mona Mohamed Abdelatty. Includes Ararbic Summary.
Impact of different torque setting on curved root canals geometry and cutting efficiency using two Ni-Ti rotary systems /
El-Gendy, Hesham Sobhi Hassan Said,; Supervisor : Abeer Hashem Mahran, Amira Galal. Includes Arabic Summary.
Machine translation output for Arabic-to-English translation of legal texts : A comparative study between AI Tools /
Reda, Dalia Ehab Abdulaziz,; Supervisor : Mustafa Riad, Sama Dawood. Includes Arabic Summary.
The effectiveness of machine translation (MT) in the legal domain requires close evaluation
using appropriate quality assessment models. This study assesses the translation quality of two
advanced MT systems, Gemini and ChatGPT by analyzing their English translations of three
Arabic Memorandums of Association. The TAUS Dynamic Quality Framework (DQF) was
adopted as the primary evaluation metric, with a focus on error typology and frequency to measure
translation performance. The research adopts a quantitative approach, examining the outputs in
terms of accuracy and fluency, while identifying and categorizing errors. A total of 1,022 errors
were recorded and analyzed: 425 in ChatGPT translations and 597 in Gemini. The findings indicate
distinct tendencies in each system: ChatGPT often omits source text content, while Gemini
exhibits a tendency toward over-translation. ChatGPT’s output showed a higher percentage of
accuracy-related errors, particularly mistranslations, whereas Gemini was more prone to over translation errors. The study underscores the ongoing necessity of human post-editing in legal
translation workflows. It also emphasizes the importance of incorporating domain-specific training
data and tailored quality assurance (QA) modules to improve MT output in legal contexts.
Ultimately, this research contributes to the growing body of literature on MT evaluation by
offering insight into the strengths, limitations, and error patterns of emerging AI-powered
translation tools. The researcher recommends further exploration of additional TAUS error
categories, such as style and locale, and calls for broader experimentation with other MT systems
to reflect the rapid development of AI in legal translation.
Keywords: Machine Translation, Legal Translation, Neural Machine Translation, TAUS Error
Typology, ChatGPT, Gemini.
Machine vs. human translation of cultural dimensions in children’s literature : Andersen and Rowling as Cases of Study /
Saleeb, Sandy Adel Nabih Rizk,; Supervisor : Fadwa Kamal, Sama Dawood. Includes Arabic Summary.
This comparative study investigates the efficacy of Machine Translation (MT) in translating
children’s literature, specifically examining its treatment of cultural references. The selected
genres for analysis are fantasy fiction and fairy tales fiction. Accordingly, the study includes short
stories by Hans Christian Andersen alongside the third book in the Harry Potter series, Harry
Potter and the Prisoner of Azkaban, by J. K. Rowling. By employing a comparative and contrastive
approach, the MT output, generated by ChatGPT, is analyzed against human translations. The
findings offer valuable insights into the effectiveness of MT in preserving cultural identity in
children's literature. The results reveal that while ChatGPT tends to produce literal translations
with minimal cultural filtering, human translators employ adaptive strategies such as omission,
substitution, and compensation to maintain cultural relevance. The study concludes that although
MT tools are rapidly advancing, they still require human oversight to handle culturally sensitive
content, particularly in texts intended for young audiences. This research ends with practical
recommendations for translators, NLP engineers, and future scholars to enhance culturally aware
MT systems in the Arab context.
Keywords: Machine Translation, Children’s Literature, Cultural Appropriation, Fantasy, Fairy
Throughput Enhancement in Wi-Fi Using SDMA Through IPS /
Elsayed, Samar Ayman Mohamed Ahmed,; Supervisor : Samy El-Hennawey, Ihab A. Ali. Includes Arabic Summary.
As communication systems continue to evolve rapidly, addressing the
challenges they encounter becomes increasingly vital. This thesis presents a
comprehensive study on enhancing the performance of Wi-Fi systems, by
giving a particular focus on integrating Space Division Multiple Access
(SDMA) with the traditional Carrier Sense Multiple Access (CSMA) protocol.
The research begins with a detailed exploration of the IEEE 802.11 standards,
providing a strong foundation for understanding their role in wireless
communication. Existing Indoor Positioning Systems (IPS) designs are
reviewed and categorized, highlighting current methodologies and technical
challenges. A specific IPS methodology is the root for the thought for utilizing
space division idea proposed in this thesis.
A novel SDMA-based approach is proposed to address network
bottlenecks caused by carrier sense mechanisms. By combining SDMA with
CSMA, the solution aims to reduce collision and contention, especially in high
user-density environments. The work involves evaluating wireless simulation
tools to identify the most effective environment for testing the proposed system.
A selected simulation tool is further customized to meet the specific
requirements of this study.
The system performance is tested through multiple simulation
scenarios. Simulations are designed to reflect real-world use cases,
incorporating randomly distributed users within various indoor layouts. Further
evaluations included expanding the simulation area, simplifying antenna
sweeping strategies, and testing the system under a broader range of user
densities.
Simulation scenarios demonstrate that SDMA significantly improves
network throughput—nearly doubling it compared to CSMA—while also
reducing frame loss, even under unfavorable user density conditions. An
expanded simulation area further tests scalability and confirms the robustness
of the SDMA mechanism across varying network loads. However, performance
gains diminish under extreme congestion, highlighting the need for context aware deployment strategies.
The results underscore SDMA’s potential as a viable enhancement for
future IPS and Wi-Fi systems, offering a foundation for continued research into
dynamic, large-scale indoor environments.
The thesis concludes by outlining future research directions, including
testing additional specialized scenarios, exploring the use of multiple phased
array antennas, analyzing diverse real-world layouts, and extending
compatibility across different IEEE 802.11 standards and spectral bands.