Deep fakes stand out to be the most dangerous side effects of Artificial Intelligence. AI assists to produce voice cloning of any entity which is very arduous to categorize whether it’s fake or real. The aim of the research is to impart a spoofing detection system to an automatic speaker verification (ASV) system that can perceive false voices efficiently. The goal is to perceive the unapparent audio elements with maximum precision and to develop a model that is proficient in automatically extracting audio features by utilizing the ASVspoof 2019 dataset. Hence, the proposed ML-DL SafetyNet model is designed that delicately differentiate ASVspoof 2019 dataset voice speeches into fake or bonafide. ASVspoof 2019 dataset is characterized into two segments LA and PA. The ML-DL SafetyNet model is centred on two unique processes; deep learning and machine learning classifiers. Both techniques executed strong performance by achieving an accuracy of 90%.

Blackboard is an Internet teaching management platform that allows a virtual learning environment via the Internet. It is the most popular system used by universities and educational institutions worldwide. However, this study is more concerned with foreign language (EFL) students' perceptions of the use of Blackboard in their courses. For this reason, we focused on 100 EFL students as respondents to the online questionnaire who attended the Language Department-College of Science and Humanities at Rumaah-Majmmah University in this research. Whereas, findings from both the survey data were analyzed by using (the SPSS Program) with the Lickert scale method showed participants had positive perceptions of the use of Blackboard technology for educational purposes. The results of students' perceptions proved the usefulness of Blackboard technology in the field of education. Hence, the suggestions of this study could be shared with other educational institutions in the kingdom.

The objective of the study was to explore Student Readiness in Online Learning Environment:  Student readiness in the online learning environment is a crucial factor in determining academic success. The research was descriptive and to attain the objectives a sample of a total of 300 students 92 male and 208 female students from the Bahauddin Zikariya University, Emerson University Multan, and The Women University Multan. The findings revealed students' overall moderate level of readiness for the online learning environment and positive attitude towards various aspects of online education.  The study findings may help institutions and teachers by providing further training to improve students' digital skills, ensuring the improvement of learning practices in new online environments, and implementing guidelines and policies.

The purpose of this research was to investigate the practices and challenges regarding mathematics laboratory in Punjab at school level. Descriptive survey design was used to collect data through questionnaire. The population was all secondary schools mathematics teachers of district Chakwal. The sample size was 60 through systematic random sampling technique. Only 5 percent of schools had mathematics laboratories but most of the schools had science and computer laboratories even did not have geometrical shapes and activity kits related to mathematics lessons. The big challenge regarding integration of mathematics laboratories was the lack of effective policy from the Government. There was no support from school management to purchase lab-related equipment and not a single period was included in the timetable for the laboratory. It was recommended that govt. may launch an effective policy regarding mathematics laboratory and school management may include three periods per week for mathematics lab work.

Time series analysis and decomposition are crucial in examining economic data as they uncover elements such as trends, and seasonal influences, within the data. However, some approaches have difficulty in accommodating complex, high-dimensional data. In this research, we investigate the possibilities of utilizing artificial intelligence (AI) tools, specifically, machine learning (ML) and deep learning (DL) for better timeliness and accuracy of economic forecasting. In some instances, it was shown how recent AI models can improve the data analysis of economic indicators (GDP, inflation, stock indices) through the accurate depiction of non-linear trends and changing seasonals. Model enhancements using AI also result in significant improvement in the accuracy of economic forecasts and provide more detailed and useful time series decomposition for economists and policymakers. This paper is a step towards more extensive use of artificial intelligence in econometric analysis and provides evidence on the feasibility of such in practical econometric studies.

Education plays a crucial role in social mobility by providing individuals with the tools to access better economic opportunities and improved social status. This paper explores the impact of educational attainment on social mobility, highlighting how it empowers individuals and bridges social classes. Through a literature review, the study establishes a direct link between education and upward mobility, particularly for disadvantaged groups. It examines formal, informal, and lifelong learning and their influence on raising living standards. The research investigates barriers to quality education economic, social, and political and how they perpetuate social inequality. Using both qualitative and quantitative methods, the study demonstrates that education is a key driver of economic and social transformation. It emphasizes the need to improve educational access, especially in underserved communities, to promote social mobility and overall societal welfare. The paper offers policy recommendations to reduce educational disparities and support lifelong learning for all social groups.

This study explores the impact of reframing, a core technique of Neurolinguistic Programming (NLP), on second language learning (SLL), focusing on reducing language anxiety and enhancing learner confidence and motivation. A quasi-experimental pre-test/post-test design was applied to a sample of 30 middle school students aged 10 to 15. Participants received a one-week NLP-based training centered on reframing strategies. Data were collected through structured language tasks and psychological surveys and analyzed using SPSS. The results showed significant improvements in learners' confidence, emotional regulation, and participation, along with a notable decrease in anxiety. These findings suggest that reframing positively influences both the emotional and cognitive aspects of language learning. This research highlights the value of incorporating psychologically informed strategies into language teaching, offering practical insights for educators seeking to foster supportive and effective learning environments.

Artificial intelligence(AI) is a well and indeed done deal, and now the AI economy is not only keeping itself alive but also being regarded as a force for transformation to transform fighting and its prediction and prevention into a global endeavor. Since it can use the power of massive data sources and machine learning and pattern recognition algorithms, AI systems can detect and warn of early signs of conflict so that decision-makers can get a head start. Much more specifically, an emphasis on data can amplify bias or produce incorrect predictions, undermining the trust in the results that AI promises to provide. There are significant ethical, political, and technical challenges to integrating AI into peacekeeping frameworks that need to be carefully walked along to use AI responsibly. It is this paper that studies those dimensions and looks to the future to analyze how AI might be distributed in conflict management.

The rapid advancement of digital technologies is revolutionizing online education, enhancing accessibility, personalization, and learner engagement. This study examines the impact of Artificial Intelligence (AI), Virtual Reality (VR), and Blockchain on online learning environments. A structured survey was conducted among students from three universities in Multan NUML, Women University, and an Education University to evaluate their perceptions, adoption trends, and associated challenges. The findings indicate that AI-powered systems improve personalized learning, VR fosters immersive educational experiences, and Blockchain enhances digital credential verification. The study revealed that over 60% of students perceived AI-based platforms as effective tools for personalized learning and 25% raised concerns about the lack of human interaction, fearing that AI-driven education could reduce opportunities for independent thinking, class discussions, and direct instructor feedback. This research highlights the need for institutional strategies to facilitate the effective implementation of these technologies, ensuring a more inclusive and engaging learning landscape.

This research examines the effects of e-learning on academic performance and student engagement in universities. Through a quantitative approach, data were gathered from a sample of 200 students drawn from a population of 1,050. Descriptive statistical procedures, i.e., mean, standard deviation, frequencies, and percentages, were used together with inferential tests like ANOVA and regression to test the association among variables. The results confirm that a reliable internet connection, access to digital devices, and technical support significantly improve students' experience through online learning.  It suggests the integration of mixed-method studies with long-term designs in terms of developing a more complete profile of online courses of study. It also recommends that the use of good teaching practices, strong student support services, and equitable institutional policies should be embraced to enhance motivation and attainment. All these conclusions are essential to teachers and policymakers who aspire to get the most out of online learning.