Addressing the associated rise in Carbon Emissions (CE) as smart cities expand becomes paramount. Effective low-carbon urban planning demands robust, precise assessments. This research introduces a cutting-edge solution via an Artificial Intelligence (AI) -driven Carbon Footprint (CF) impact assessment. A detailed dataset, collected over 3 years, was harnessed to gather insights into vital urban factors, including CE, Energy Consumption (EC) patterns, variations in land use, transportation dynamics, and changes in air quality. The cornerstone of this research is developing the Multi-modal Stacked VAR-LSTM model. This model proposes to provide accurate CF predictions for urban environments by merging the capabilities of Vector Autoregression (VAR) with Long Short-Term Memory (LSTM) neural networks. The process encompasses dedicated assessments for each data segment, harnessing VAR to delineate interdependencies and refining these predictions with the LSTM network using the residuals from the VAR analysis. By interweaving AI-driven carbon footprint impact assessments into the urban planning discourse, this study underscores the vast potential in sculpting future urban development strategies that are sustainable and sensitive to carbon impact.

The COVID-19 disease caused by the SARS-CoV-2 virus was declared by the World Health Organization (WHO) as a spreadable viral disease. During the COVID pandemic, there was difficulty in notifying the Decision-Making System (DMS) about the rapid and precise triage of patients admitted to the emergency wards. As a method to achieve the aim and develop digital healthcare revolutions in data and analytics, digital healthcare information was established. Artificial Intelligence (AI) is a robust automation tool for sustainability in the context of the COVID-19 health crisis on big datasets. Besides, the gap between AI investment and commercial real-time application, which are the initial digital technology development curves, has been identified. It was discovered that AI’s new applications are grounded in Digital Transformation Mapping (DTM) for the DMS of Health Crises. The fast inventions in AI and Machine Learning (ML) have implications for amazingly preventive and clinical healthcare, and for the association, ML was developed as a predictable attention. Billions of smartphones, massive online datasets, linked wireless wearable devices, comparatively cost-effective computing resources and improved ML and Nural Language Processing (NLP) are leveraged by these rapid responses, with the trained dataset of 65% and evaluated in the other 35%, the renowned ML models for structured data like Support Vector Machine (SVM), Multinomial Naive Bayes (MNB), Logistic Regressive Tree (LRT), Decision Tree (DT), Stochastic Gradient Booster (SGB), and Random Forest (RF) are used for simulating new unidentified data. AI-DTM challenges DMS of Health Crises (COVID-19) and the drawbacks of critically contributing risk factors to healthcare diseases. Meanwhile, a comprehensive collection of healthcare datasets over what is spreadable would be required to save human lives, train AI, and limit cost-effective health risks.

The rapid integration of information and communication technologies (ICT) in higher education has brought about transformative changes to traditional teaching and learning practices. This chapter examines the multifaceted impacts of ICT in the higher education sector. Over the past two decades, ICT has revolutionized the way educational institutions operate, impacting teaching methodologies, student engagement, and administrative processes. In the realm of pedagogy, ICT has facilitated the shift towards student-centered learning, empowering learners with access to diverse digital resources and interactive learning platforms. Moreover, administrative tasks within higher education have been streamlined through the adoption of ICT, resulting in enhanced efficiency in enrollment, record-keeping, and communication between stakeholders. This optimization allows educators to focus more on instructional design and student support, fostering a conducive learning environment.

This study examines the effectiveness of the Inquiry-Based Scientific Problem Learning (PBL) model in enhancing cadets’ critical thinking and learning outcomes at the Sekolah Tinggi Intelijen Negara (STIN). Addressing the evolving needs of the intelligence sector, which demands technical expertise and higher-order thinking, the research combines scientific inquiry with PBL to create a comprehensive instructional approach. A quasi-experimental design involved 50 fourth-semester cadets divided into experimental and control groups. Learning outcomes were evaluated through pre-test and post-test assessments, focusing on cognitive, affective, and psychomotor domains. Results showed that using the Inquiry-Based Scientific Problem Learning model, the experimental group achieved significant gains in all areas. Cadets in the experimental group demonstrated enhanced critical thinking and analytical skills in the cognitive domain, increased motivation, communication, and collaboration in the affective domain, and superior practical skills in the psychomotor domain. Statistical analyses, including N-gain, validated the model’s impact. These findings suggest that the Inquiry-Based Scientific Problem Learning model effectively develops intelligent professionals, bridging theory and practice while fostering technical and soft skills crucial in the field. This research supports the need for innovative and adaptive educational methods in specialized and dynamic environments like intelligence education.

Introduction: This study investigates the impact of 5G technologies, technological and environmental factors, and parental and community support on the educational performance of high school students in Jordan. Educational outcomes must be understood because modern technological systems alongside community involvement need assessment during this COVID-19 era of digital learning tool dependency. Researchers investigate here how educational variables enhance student academic achievements under present-day digital learning models.Methods: A survey included 300 students across ten high schools throughout different Jordanian regions. The study relied on Partial Least Squares Structural Equation Modeling as its data analysis foundation through SmartPLS software implementation. A statistical analysis evaluated the link between 5G technologies, technological and environmental factors, and parental and community support which act as independent variables towards educational performance as the main dependent variable.Results: The study showed 5G technologies combined with both technological and environmental factors together with parental and community support have positive effects on educational performance measurement. The analysis through path coefficients and p-values showed that all variables lead to better student learning experiences with positive academic results. Specifically 5G technologies enabled interactive learning but additional student achievement came through digital resource access together with parental involvement.Conclusions: The study summarizes its findings by establishing that inserting 5G technologies together with improved environmental factors and enhanced technological factors plus support from parents and communities actually drives education success. Schools need to focus first on building strong digital infrastructure for learning purposes and secondly on building interconnections between parents and local communities to support student education. The evaluation of these elements' sustained influence on educational outcomes must occur through future investigations which should analyze both cultural diversity and geographical scope while examining how distinct intervention methods build these educational components globally.

As the world becomes increasingly interconnected through digital advancements, the rapid growth of electronic commerce (e-commerce) has revolutionized the global economy. E-commerce platforms have become instrumental in facilitating financial transactions, reshaping trade dynamics, and fostering economic growth. However, this digital paradigm shift has brought along significant cybersecurity challenges that threaten the integrity and stability of e-commerce systems. This research paper delves into the critical role of cybersecurity in e-commerce to achieve the Maqasid of Money - the preservation and promotion of wealth in Islam. The study investigates the multifaceted dimensions of e-commerce and the evolving threats posed by cyber-attacks that have far-reaching consequences for financial transactions, consumer trust, and overall economic prosperity. The research employs a comprehensive literature review to explore the fundamental principles of Maqasid al-Shariah concerning wealth protection and the ethical considerations governing financial interactions in Islam. Additionally, it examines the evolving nature of cyber threats, such as data breaches, identity theft, payment fraud, and denial-of-service attacks, which can disrupt e-commerce operations and undermine the trust between stakeholders. To address these challenges, the research underscores the importance of robust cybersecurity measures in e-commerce platforms. Various cybersecurity strategies and technologies, including encryption, multi-factor authentication, intrusion detection systems, and secure payment gateways, are evaluated in light of their potential to safeguard financial transactions and uphold the Maqasid of Money. Furthermore, the paper analyzes case studies of successful cybersecurity implementations in prominent e-commerce enterprises to discern best practices and learn from their experiences. It also discusses the role of regulatory frameworks and international cooperation in combating cyber threats in the e-commerce domain. The findings of this research highlight the critical interplay between cybersecurity and the Maqasid of Money in e-commerce. By fortifying the security posture of e-commerce platforms, stakeholders can foster an environment of trust, transparency, and reliability that aligns with the Islamic principles of financial integrity and accountability. Ultimately, this research contributes to the growing body of knowledge on cybersecurity and its ethical implications in e-commerce, aiming to empower policymakers, industry practitioners, and scholars to devise strategies that harness the transformative potential of digital trade while safeguarding the core principles of Islamic finance.