The approach to delivering education in Libya has undergone a significant transformation in recent years. Various tools now support the educational process, shifting it from rote learning to creativity, interaction, and skill development. This study aims to examine the feasibility of implementing e-learning in Libyan universities. A statistical analysis was conducted on approximately 400 samples to identify patterns. The findings highlight the importance of e-learning in enhancing the quality of education by outlining its benefits and limitations. Moreover, it was found that employees consider e-learning an effective alternative to traditional education. Despite this consensus, concerns remain regarding the availability of sufficient infrastructure. 

In recent years, higher education has witnessed a significant shift toward digital environments, with e-exams becoming an essential tool for academic assessment due to their speed, efficiency, and reduced administrative burdens. However, the adoption of e-exams in Libyan educational institutions, particularly at the Faculty of Science in Gharyan, still faces challenges stemming from technical, organizational, and human factors. This study aimed to explore the main challenges hindering the implementation of e-exams and analyze the potential role of blockchain technology in enhancing security and reliability. A descriptive methodology was employed, with data collected through a questionnaire distributed to faculty members. Results revealed that the most significant barriers included weak ICT infrastructure, a lack of administrative and technical support, and the absence of reliable and user-friendly e-exam systems. Additional challenges included unclear policies, a lack of awareness of the benefits of e-exams, and concerns about cheating and technical glitches. On the other hand, individual factors, such as resistance to change and the difficulty of designing e-exams, showed a relatively smaller impact. The findings highlight the need for stronger infrastructure, ongoing training, and clear institutional policies as prerequisites for the successful adoption of e-exams. Furthermore, the integration of blockchain technology offers a promising solution by ensuring consistent exam records, secure student identity verification, and transparent assessment processes. The study concludes that developing more reliable and effective e-assessment systems in Libya requires collaboration between technical and Libyan educational institutions, with blockchain technology considered a strategic option for enhancing trust and security in higher education.

Abstract The integration of Artificial Intelligence (AI) in education is progressively transforming teaching, learning, and administrative practices globally, with significant potential for application in Libya. the purpose of this research is to discuss and evaluate the benefits and risks of AI in the education system of Libya. To achieve this, a descriptive research approach was employed, using a questionnaire distributed to a selected group of educational professionals in Libya. The sample consisted of 1,000 participants, and the survey was conducted via the WhatsApp application. The results highlight that personalized learning received the highest mean score of 4.19, indicating strong agreement on its effectiveness. Automation of administrative tasks (mean 3.80) and data-driven decision-making (mean 3.98) also showed favorable perceptions, with low variances around 0.24 0.25, reflecting consistent responses. Improved student engagement had a mean of 3.91 and a standard deviation of 0.49, similar to others, suggesting overall positive and uniform attitudes. Additionally, most responses clustered around neutral to moderate agreement, with modes of 3 or 4, showing balanced or mildly supportive opinions. Variance values ranging from 1.39 to 1.48 suggest a moderate spread, indicating some disagreement among participants. Standard deviations around 1.18 to 1.21 confirm a consistent yet moderate level of variability, without extreme polarization The obtained results show strong agreement on the benefits of educational innovations, especially personalized learning, which had the highest mean, and all aspects scored highly with low variability, indicating consistent positive perceptions. At the same time, the conclusions reveal moderate concern among respondents about the cost and inequality issues related to AI in education, with variance and standard deviation values reflecting a consistent spread of opinions. This research contributes to the academic discourse on the impactful integration of AI in academic institutions and establishes positive perceptions for continual enhancement. Overall, funding infrastructure emerges as the most pressing challenge, with general agreement across participants. Keywords. Artificial Intelligence, Education, Personalized Learning, Libya. 

Dyslexia is a distinct learning disability that is distinguished by difficulties in decoding and reading fluency, spelling as well as other cognitive skills. This research is conducted to assist learning disability by improving the skills required for children with learning disability in reading and spelling using the assistive technology AVA interactive whiteboard. The approach is by strengthening the micro skills required to improve the fundamental skills such as reading, and spelling thus facilitating the learning process. Tactile and visual modalities are the main focus in the use of the interactive whiteboard. This study aims to develop an interactive whiteboard learning prototype for students with dyslexia. A total of six children from 3 demographics (Chinese, Malay, and Indian) participated in the study. Activities improving the four micro skills were introduced in normal whiteboard and the children were exposed to the prototype AVA interactive whiteboard. Responses using Interactive whiteboard were different when compared to their performance with the normal whiteboard. The analyzed results indicated showed improvements in three of the micro skills using IWB

Abstract: This paper focuses on the challenging task of counting the number of people in digital still images, which has important applications in many fields such as security, management, education, and commerce. This paper proposes a system that is based on the Viola-Jones face detection methods. This system consists of two parts: a) face detection and b) counting the detected faces. In the face detection part, the Viola-Jones (LBP and CART feature extraction) algorithm is applied to the input image. In the counting part, the detected faces are counted to estimate the number of people in the given image. The Viola-Jones algorithm is applied using 133 images from the People Image Groups dataset, and the best precision achieved is 96.9%. Overall, this paper presents a promising system for accurately counting the number of people in digital static images using a simple and costeffective approach

This systematic review investigates the impact of the COVID-19 pandemic on cybersecurity by examining the rise of cyberattacks targeting financial institutions. By analyzing over 60 sources including academic research, government reports, and security company data, the review reveals a nearly two-fold increase in cybercrimes targeting financial institutions during the pandemic compared to pre-pandemic levels. Phishing attacks are identified as the most prevalent form of cybercrime within this context. The review delves further by analyzing the differences between phishing and other cyberattacks during COVID-19. Based on the results and observations presented in this paper, the analysis will contribute to enriching strategies to address the growing threat of cybercrime in the financial sector

Background and aims

In recent years, the education sector in Libya have been affected by wars and political fluctuations, impacting the quality and availability of education. There have been challenges in providing the necessary educational resources, as well as in training and qualifying teachers. E-learning, it can be an effective tool in improving education under difficult circumstances. Online education can provide opportunities for students to access educational resources easily, and can contribute to enhancing communication between teachers and students. E-learning can also play a role in developing students’ technology skills, which is important in our modern era. In 2019, the Faculty of Science at the University of Gharyan partially implemented online learning as a response to COVID-19 pandemic, and this program continued for two academic terms. Therefore, the paper aims to highlights both the advantages and limitations of E-learning within the environment of university education in Libya

This study delves into the evaluation of daily profits within the network of Sephora cosmetics branches, employing distributed systems, the K-means algorithm, and WEKA visualization techniques. The objective is to analyze the profitability patterns across Sephora branches and uncover underlying clusters to optimize strategic decision-making. The research methods encompassed the utilization of distributed systems to collect and integrate daily profit data from multiple Sephora branches. The K-means clustering algorithm was applied to segment the dataset, discerning distinct clusters based on profit margins and performance metrics. The WEKA visualization tool was instrumental in depicting these clusters in a comprehensive and interpretable manner, offering insights into profit distributions and potential areas for enhancement. This research revealed intricate profitability structures within the Sephora branch network. The application of the K-means algorithm, distinct clusters of branches with varying profitability profiles were identified. WEKA visualization facilitated the graphical representation of these clusters, elucidating the relationships between different branches based on daily profits. Such insights can aid decision-makers in strategizing resource allocation, marketing initiatives, and operational improvements tailored to each cluster's profitability dynamics. The amalgamation of distributed systems, K-means algorithm, and WEKA visualization offered a robust framework for assessing and optimizing the financial performance of  Sephora branches. This research contributes valuable insights into the evaluation of daily profits across  Sephora cosmetics branches, showcasing the potential of distributed systems and advanced analytical tools in understanding profitability patterns. The findings provide a foundation for strategic interventions aimed at enhancing profitability and operational efficiencies within the Sephora branch network.

Abstract:

In this research study, we investigate the effectiveness of a proposed automated framework that leverages AI algorithms to improve the accuracy, scalability, and efficiency of data analysis. We compare the performance of the proposed framework to traditional data analysis methods in terms of accuracy, time and effort required for data analysis, and scalability. We conducted a questionnaire-based survey to collect data on the application of the proposed framework and traditional data analysis methods in real-world scenarios. We used statistical analyses, including t-tests and regression analyses, to analyze the data and draw conclusions. Our findings indicate that the proposed automated framework outperforms traditional data analysis methods in terms of accuracy, reduces the time and effort required for data analysis, and has better scalability for processing large datasets in real-time. Our results suggest that the proposed framework offers significant benefits for organizations seeking to improve their data analysis processes. However, we also note the importance of considering the costs and benefits of implementing the framework, as well as any ethical or legal implications. Further research is recommended to confirm the findings and to investigate the effectiveness of the proposed framework in different contexts and with different datasets.