This study will employ a mixed methods approach to investigate postgraduate engineering students' success within the Egyptian higher education context. The research examines six hypotheses related to success factors: the impact of academic background, psychological attributes, scholarly environment, research capabilities, external circumstances, and personal traits. Quantitatively, multivariate regression analysis examines the relationship between student success (measured through a composite score of publications, thesis quality, graduation time, and professional achievements) and corresponding predictive variables including CGPA, grit scales, laboratory access, critical thinking assessments, financial stability indicators, and leadership metrics. Qualitatively, in-depth interviews with faculty and students explore how these factors interact and influence academic outcomes. Data collection combines academic records, psychological assessments, and institutional surveys with thematic analysis of interview transcripts. The quantitative phase employs statistical measures to test the hypotheses, while the qualitative phase provides rich contextual insights into how these factors manifest within Egypt's unique educational landscape. This integrated approach aims to validate which factors most significantly predict postgraduate success, thereby informing evidence-based policies for student selection and support systems.

This study explores the influence of grit-defined as perseverance and passion for long-term goals-on the academic success and retention of first-year engineering students in Egypt. Approximately 300 students from various universities will be randomly selected to ensure a diverse demographic sample. At the start of the academic year, participants will be evaluated using a modified version of Angela Duckworth's 12-item Grit Scale, and their academic performance and retention will be monitored throughout the year. The study will utilize statistical methods such as correlation and regression analyses to investigate the link between grit and academic success, including GPA and course completion rates. Additionally, qualitative data from follow-up interviews will provide insights into students' experiences and factors influencing their decisions to continue or leave their studies. The expected outcomes include a comprehensive understanding of grit levels among students, its predictive power for academic success and retention, and recommendations for interventions to cultivate grit. The findings aim to inform educational practices and policy, enhance student support services, and potentially reduce dropout rates. This research could serve as a foundational study for future longitudinal investigations of the long-term effects of grit on educational and career achievements.

This paper presents an advanced encryption algorithm specifically designed to enhance the security of volumetric medical image data, crucial for the Internet of Medical Things (IoMT). The algorithm encrypts a stack of 256 images, each with dimensions of 256×256 pixels, through a meticulous multi-stage process. It begins by segmenting an image cube into Red, Green, and Blue channels, which are then encrypted through three phases: XOR operations with keys from an 8D hyperchaotic system, substitution with S-boxes derived from Gold sequences, and a final transformation using Fibonacci Q-matrices. This approach significantly improves security by improving entropy, decreasing cross-correlation, and strengthening resistance to statistical attacks, with various cryptographic seeds used at each stage to enhance the robustness of the encryption. Specific performance evaluation metrics include a pixel cross-correlation of approximately 0, an NPCR of 99.61%, a UACI of 34.45%, an entropy of 7.998, and a key space that exceeds 22870. Extensive cryptographic assessments confirm the effectiveness of this algorithm, making it a vital tool for securing medical image data within IoMT, ensuring safe transmission and storage in healthcare systems.

This research aims to uncover the pivotal ele-ments that contribute to the success of engineering students in their inaugural academic year. To achieve this, we will investigate the influence of numerous intrinsic and extrin-sic factors, treating them as independent variables in our study. Our methodology is grounded in quantitative research techniques, and our primary source of data will be surveys distributed amongst first-year engineering students attending private universities in Egypt. The survey will encompass a wide variety of factors. On the student side, we will consider variables such as age, gender, preexisting notions and perceptions, prior knowledge, study habits, parental education, and ethnicity. Simultaneously, we will also examine institutional factors like the curriculum's design, the pedagogical expertise and scientific knowledge of the professors, as well as the quality of academic support services available to students. The collected data will be subjected to a comprehensive statistical analysis using multivariate regression techniques. The objective of this rigorous analysis is to glean valuable insights into the key determinants of success for first-year engineering students within Egypt's private university system. The results of this study are expected to significantly augment our understanding of the factors that drive student success. This, in turn, will be instrumental in formulating effective strategies to enhance student outcomes. Furthermore, the findings promise to enrich the existing body of literature on engineering student success and could serve as a valuable reference for future research in this domain.

Abstract This research work presents a novel secured spatial steganography algorithm consisting of three stages. In the first stage, a secret message is divided into three parts, each is encrypted using a tan logistic map encryption key with a unique seed value. In the second stage, the encrypted parts are transformed into quick response codes, serving as a layer of channel coding. Subsequently, the quick response codes are decoded back into bit‐streams. To enhance security, a uniquely‐seeded Mersenne Twister key is generated and employed to apply DNA coding onto each bit‐stream. The resulting bit‐streams are then embedded in the least significant bits of the RGB channels of a cover image. Finally, the RGB channels are merged to form a single stego image. A comprehensive set of experimental analyses is conducted to evaluate the performance of the proposed secure steganography algorithm. The experimental results demonstrate the algorithm's robustness against various attacks and its ability to achieve high embedding capacity while maintaining imperceptibility. The proposed algorithm offers a promising solution for secure information hiding in the spatial domain, with potential applications in areas such as data transmission, digital forensics, and covert communication.

Contribution: This paper identifies key motivational influences affecting students’ choice of one of the following majors: electrical, computer and mechatronics (ECM). The findings support prior research carried out in domains other than engineering.Background: Given various ECM majors to choose to pursue, students are motivated and influenced by a number of factors to choose one major over the others.Research Question: What are the motivational influences relating to engineering students’ major selection?Context: This study is carried out at a private higher education institution (HEI) in Cairo, Egypt.Methodology: A quantitative study is carried out, utilizing a survey and gathering 309 responses. Correlation as well as regression analyses are carried out, identifying which constructs have a significant effect on students’ choice of engineering major.Findings: Financial motivations have a paramount significance for students when deciding which engineering major to select. Other factors identified, in order of their significance, are mentor influences, intrinsic motivations and social good motivations.

The ever-evolving nature of the Internet and wireless communications, as well as the production of huge amounts of multimedia every day has created a dire need for their security. In this paper, an image encryption technique that is based on 3 stages is proposed. The first stage makes use of DNA encoding. The second stage proposed and utilizes a novel S-box that is based on the Mersenne Twister and a linear descent algorithm. The third stage employs the Tent chaotic map. The computed performance evaluation metrics exhibit a high level of achieved security.

With the recent amelioration in digital communication and cloud storage, security remains a concern. Even though cryptographic algorithms have been readily used, they have been proved to be vulnerable to brute force and side channels attacks. Hence an additional security layer must be integrated to overcome the suspicion introduced by cryptography which is only concerned with the secrecy of the transmitted data. Adjacently, steganography tackles the secrecy of communication in the first place and hence a hybrid double layer security scheme that integrates both systems safeguards the data in terms of secrecy and imperceptibility. In this paper, we propose a double layer blind reversible security scheme which deploys Blowfish encryption as a cryptographic layer followed by a least significant bit image steganographic layer which spreads the encrypted secret data required to be transmitted over the pixels of an image cover medium. Our scheme also spreads the data again over the color channels of the pixels selected for embedding according to a gray code sequence. In order to judge the performance of our proposed scheme, the values of peak signal to noise ratio, mean squared error and structural similarity index have been computed and compared to other least significant bit schemes in the literature. The proposed scheme has been proved superior in terms of capacity, imperceptibility and computational complexity.

A comparative study on the theoretical bit error rate (BER) is presented for hybrid relaying schemes that toggle between adaptive decode-and-forward (ADF) and amplify-and-forward (AF) protocols, for a typical three-node wireless network. Toggling between the two forwarding protocols is based on the log-likelihood ratio (LLR) or the signal-to-noise ratio (SNR) of the received signal at the relay node. Closed-form expressions for the probability of error are presented, as well as the expressions of the proposed schemes’ gains over classical ADF and AF protocols. Comparisons are carried out among the two schemes and other hybrid schemes found in the literature. Moreover, the impact of relay location on the probability of error is investigated.