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Recent Submissions

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Advanced analytical techniques for measuring some important antidiabetics in dosage forms and Bio-fluid samples /
Tantawy, Merna Abdelrasoul Mohamed,; Supervisor : Rasha Mahmoud Ahmed, Randa Abdel-Salam, Noha Ibrahim Shaaban. Includes Arabic Summary.
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Comparison of fracture resistance of endodontically treated molars restored by two different restorative techniques : An in vitro study /
Amer, Esraa Mohamed Mahmoud Sayed,; Supervisor : Mohamed Adel Ezzat Khairy, Ola Ibrahim Fahmy, Ahmed Mohamed Hosney Fayed. Includes Arabic Summary.
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The effect of visual communication on consumer attitudes towards brands : A comparative study on selected advertisements before and during pandemic /
El-Sardy, Amina Alaa Mohamed Ibrahim,; Supervisor : Aliaa El Turafy, Dina Orabi. Includes Arabic Summary.
A brand’s visual communication is the identity that differentiates one brand from another. Using visual communication effectively is the key to brand survival in normal conditions and most importantly during pandemics. People around the world faced multiple pandemics throughout the past years such as Swine Flu in 2009, and the latest pandemic that hit the whole world intensively was the Covid-19 virus in 2019. Accordingly, Covid-19 will be the case study examined in this thesis paper as the main core is how brands communicate visually in pandemics. During Covid-19 pandemic, people were in quarantine for a couple of months. Some of the global brands have been forced to adapt to the new circumstances and figure out how to achieve continuity & survival of their brands during the pandemic and encourage their consumers to get over it too. As a result, some brands have broken the rules and made temporary changes in their visual communication tools (including logos, slogans, colors, advertising messages, visuals and hashtags) to cope with the Covid-19 pandemic. Hence, this study aims to detect and analyze the effect of the change in brands visual communication that took place during the Covid-19 pandemic on consumer attitude. This study adopts the Semiotics Theory as its assumptions and developments serve and suit the topic. Additionally, a mixed-methods research approach is employed in this study, which combines both a quantitative online survey with 403 respondents, a qualitative content analysis on 6 advertisements 9 months before and 9 months during the pandemic on 6 categorical variables and qualitative in-depth interviews with 3 experts in the advertising field. The results show a statistically strong correlation between noticing visual communication changes and the consumers’ attitudes. The study also sheds light on the importance of changing the visual communication strategies of brands which should be examined, further in future studies.
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Effect of two different surface treatment protocols and resin cement viscosities on shear bond strength of advanced lithium disilicate after thermocycling : (In vitro study) /
Thabet, Yomna Ezzuldin Mohamed,; Supervisor : Ashraf Hassan Mokhtar, Hanaa Hassan Zaghloul, Mostafa Hussien. Includes Arabic Summary.
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Effect of changes in sintering parameters on color reproduction and translucency of multi-phase zirconia : (In-vitro study) /
Abdelrahman, Abdelrahman Amir Rashad,; Supervisor : Hesham Katamish, Tarek Salah, Yara Sayed Attia. Includes Arabic Summary.
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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.
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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.
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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.
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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.