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Recent Submissions
The Role of consumer socialization in the process of advertising literacy among Egyptian children : A comparative study between perceptual and analytical stages /
Louis, Julie Emad,; Supervisor : Nagwa El Gazzar, Dina Orabi. Includes Arabic Summary.
During this technological era, children are born into an environment that is saturated with
different forms of advertising including the embedded formats, and they have become highly
targeted by advertisers as they form a potential segment of the market. Consumer Socialization
Theory explains the stages children pass through and the socialization process by which they
acquire skills, knowledge, preferences and attitudes that allow them to function as valuable
consumers in the marketplace. Advertising literacy is one of the most important skills acquired
throughout this process and it acts as a defense mechanism against the negative impacts of
advertising on children, empowering them to deal with the commercial messages without
harming their development process. This interdisciplinary research aims to investigate the role
consumer socialization plays in the process of acquiring and activating advertising literacy
among Egyptian children across two different consumer socialization stages, the Perceptual stage
(ages 3 to 7) and the Analytical stage (ages 7 to 11). Consumer Socialization Theory and
Malmelin’s model with its dimensions of advertising literacy are utilized as the theoretical
framework for this research. Both qualitative and quantitative approaches are implemented in
this study through structured surveys for children based on Advertising Literacy Scale for
children (ALS-c), and another one for parents, and focus groups for more insights with mothers.
The findings of this study shows that children of both stages are having almost equal abilities
conceptual advertising literacy indicating that both stages are facing real challenges to
cognitively deal with the new embedded advertisement formats. Analytical stage children were
found to develop a slightly higher level of Attitudinal advertising literacy, however their level of
responsiveness to the persuasion messages of the embedded advertising questions their ability to
utilize these skills for their own benefit.
Influence of implant abutment materials on the final color of two anterior implant-supported restorations : in-vitro Study /
Salama, Ingy Yehia Mokhtar,; Supervisor : Hanaa Zaghloul, Mohamed Eldemellawy, Yara Sayed Attia. Includes Arabic Summary.
Effect of contracted access cavity preparation on procedural errors in curved root canals in molars : An in-vitro study /
Zakhary, Marina Hesham Fawzy,; Supervisor : Salma Al-Ashry, Nihal Sabet, Ahmed Khalaf. Includes Arabic Summary.
Evaluation of fracture resistance of maxillary premolars with MOD cavities restored with different dentin replacement techniques : An in-vitro study /
Assar, Sara Magdi Ali Moustafa,; Supervisor : Khalid Mohamed Noaman, Inas Mohsen Gameel El Zayat, Mohamed Essam Mohamed Labib. Includes Arabic Summary.
Chemico-mechanical retrieval of two bioceramic based obturation techniques : (In vitro) /
Awad, Passant Gaber,; Supervisor : Kareem Mostafa Al batouty, Mohamed Mokhtar Nagy, Ahmed Hussein Abuelezz. Includes Arabic Summary.
The Representation of ancient Egyptian history in global animated cartoons : A comparative study of Egyptian, American, and Japanese Animated Cartoons /
Alamr, Maha Mansour Abdullah,; Supervisor : Mohamed Hossam Ismail, Amr Mohamed Galal. Includes Arabic Summary.
Ancient Egyptian history is represented in global animated cartoons. This study
investigates the representation of ancient Egyptian history in Egyptian, American and Japanese animated cartoons. The research analyzes and compares the animated cartoons with ancient Egyptian representation in each production country. The study conducted qualitative and quantitative methodology techniques. By using qualitative and quantitative linguistic discourse analysis. Besides, using qualitative semiotic analysis of Nine animated cartoons, Three animated cartoons from each production county.
Results of the study found that there are several differences in there presentation of ancient Egypt among the Egyptian, American, and Japanese animated cartoons. The qualitative results showed that the Egyptian animations primarily focused on providing historical information, specifically about ancient Egyptian queens and kings. American animations focused on representing ancient Egyptian temples as places for magic and demons. Japanese animations took a different approach, by focusing on representing ancient Egyptian deities and provided information about their responsibilities. In all the three countries of production the ancient Egyptian culture was mixed with other cultures such as American, Japanese, and European cultures. Also, it showed that there are many differences between the representation of ancient Egyptian characters in animated cartoons and in history.
The quantitative results showed that the most represented personality in Egyptian animated cartoons is the friendly personality, the percentage is 25%. The most represented personality in American animated cartoons is the aggressive personality, the percentage is 35%. The most represented personality in Japanese animated cartoons is the strong personality, the percentage is 22.5%. Additionally, research findings proved that there is a correlation between roles represented by ancient Egyptian characters and the country of the production.
An Artificial intelligence-based system for automatic diagnosis of siseases via EEG signals /
Hanafy, Mennato-Allah Talaat Mostafa,; Supervisor : Medhat Hussein Ahmed Awadalla, Lamiaa Sayed Abdel-Hamid. Includes Arabic Summary.
Alzheimer’s disease (AD) is known for being the main type of dementia,
distinguished by developing descent in cognition and amnesia. Early diagnosis can
assist in disease management and enhance patients’ overall quality of life.
Electroencephalogram (EEG) has emerged as a non-invasive tool for detecting AD
that has the benefit of having a high temporal resolution. AD causes several significant
changes to the patients’ EEG recordings including reduced complexity, slower EEG
rhythms, and changes in synchrony. This thesis explores the use of EEG signals
combined with machine learning techniques to develop a computer-aided diagnosis
(CAD) tool for the improvement of AD diagnosis. Although Recurrence
Quantification Analysis (RQA) features have demonstrated promising results in
various EEG analysis methods such as emotion detection, they have been scarcely
implemented for AD detection. In this thesis, RQA features are computed to
investigate their usefulness for AD detection. Specifically, four feature groups are
considered for the detection of AD from EEG recordings which are (1) RQA, (2)
Hjorth, (3) Statistical, and (4) Power Spectral features. Multiple classifiers are
compared including Support vector machines (SVM), K-Nearest Neighbors (KNN)
and Random Forest (RF). Cross-validation (CV) methods, such as 10-fold and leave one-subject-out (LOSO) CV, are used to evaluate model performance. For
investigating the relevance of features extracted from original EEG vs. from
decomposed EEG, results reveal that features extracted from decomposed brain
frequency sub-bands significantly enhance classification accuracy when compared to
those extracted from the original EEG signal. An improvement ranging from 7% to
25% is observed for 10-fold CV and from 4% to 16% for LOSO CV. Next, two feature
selection methods are applied and compared. In general, both feature selection
methods yielded consistent results, leading to performance improvement by 1% to 3%
in all experiments. Throughout all performed investigations, RQA features results in
II
the best accuracies in which its accuracies outperform Hjorth, Statistical and Power
Spectral features with up to 15% and 25% for 10-fold CV and LOSO CV,
respectively. These results highlight the usefulness of RQA features for AD detection
from EEG signals. Best results are achieved by combining best-performing features
from RQA and statistical group of features extracted from the decomposed EEG
signals in which achieved accuracies were 99.2% and 96.7% for 10-fold CV and
LOSO, respectively, using the SVM classifier. This research contributes to the
development of more reliable AD diagnostic tools and highlights the potential of
EEG-based methods in clinical practice.
Open City Museum: Al Ismailia City. Egypt
(2024) Gadalla, Pierre.
A TALE OF TWO CITIES
(2024) Rabiee,Youssef Hesham.
Nexus: incubate to communicate
(2024) Ayman, Yosr.