2692-4048ISSN (Online)
2770-0070ISSN (Print)
This study delves into the relationship between cyber-physical systems (CPS) and economic security, with particular emphasis on how networking technologies facilitate more efficient data integration. It investigates how CPS adoption is reshaping national economies by influencing productivity levels, altering labor market structures, and introducing new cybersecurity challenges. Employing a hybrid research design that merges cross-sectional data evaluation with expert consultations, the research offers a comprehensive view of the implications of CPS implementation on sectoral productivity, employment trends, and macroeconomic resilience.CPS are positioned in the study as strategic innovations powered by data intelligence, underlining both their promising opportunities and associated threats. The findings support the development of informed policy measures that aim to enhance benefits while reducing potential risks. Ultimately, the work contributes to the evolving discourse on CPS by offering a balanced analysis of their socio-economic impacts and outlining actionable recommendations for decision-makers and industry stakeholders to capitalize on CPS innovations effectively.
Read MoreDoi: https://doi.org/10.54216/FPA.200101
Vol. 20 Issue. 1 PP. 01-11, (2025)
Data compression technologies play a big role in various areas where efficient data storage and transmission are essential. Data compression is the science of reducing redundant data to a compact form, which used to safely store files or information. On the other side, Unicode is a global standard for the representation of text and symbols in computers. The basic elements of the Unicode standard are code points, which represent a specific symbol. Unicode provides a unified way to map and manage these points to ensure consistent representation and interpretation of text data across different systems, platforms, and languages. This paper proposes a method to compress texts in Arabic, based on Unicode ligatures, which typically join characters together. This method replaces two or more Unicode Arabic ligature characters with a single Unicode Arabic ligature based on their appearance in the Arabic text file, eliminating the need for coding or decoding. The size of the original and output text files has been compared to show the percentage of compression. The selected dataset: Modern Standard Arabic text involves Arabic news, and Classical Arabic text involves Arabic Holy and Honorific text collected from Kaggle. The percentage of compression depends on the frequency of ligature characters in Arabic documents. Unfortunately, the results were not promising, as the method was only able to compress the file to a very small percentage (6.71 %and 12.82 %, respectively, for Arabic news and Arabic Holy text). We think that the proposed method can be improved by using a hybrid technique of text compression in the future; in addition, consider other properties of Arabic Unicode. Programming can express competency concepts in a well-defined mathematical model for a particular.
Read MoreDoi: https://doi.org/10.54216/FPA.200102
Vol. 20 Issue. 1 PP. 12-23, (2025)
The hospitality industry is rapidly evolving, with intense competition among organizations striving to attract and retain customers. One of the key factors influencing customer satisfaction and loyalty is the emotional intelligence of employees. Higher emotional intelligence fosters positive behavior, which enhances customer experience and engagement. This study aims to identify and prioritize the most critical factors and sub-factors of emotional intelligence in the private hospitality sector. Data for this research has been collected from hospitality businesses in the Lucknow region. The prioritization process is carried out using the Analytical Hierarchy Process (AHP), a widely used multi-criteria decision-making (MCDM) technique. The rankings derived from AHP provide valuable insights into the key attributes of emotional intelligence that employees should focus on for professional growth. By understanding these priorities, hospitality employees can enhance their emotional intelligence, leading to improved customer interactions, better teamwork, and overall organizational success.
Read MoreDoi: https://doi.org/10.54216/FPA.200103
Vol. 20 Issue. 1 PP. 24-33, (2025)
Visible light communication (VLC) integrated with nonorthogonal multiple access (NOMA) is a promising technique to meet the increasing demand for high capacity, energy-efficient communication in forthcoming 6G networks. This work thoroughly evaluates VLC-NOMA systems and emphasizes the incorporation of machine learning (ML) approaches to improve spectrum efficiency, the bit error rate, and resource allocation. A technique based on Preferred Reporting Items for Systematic Reviews and Meta-analyses produced 244 records, among which 45 were selected for comprehensive study. The review identified obstacles, including scalability, computational complexity, and insufficient experimental validation. A comparative examination elucidated the strengths and limits of machine learning methodologies, including machine learning, deep neural networks, and federated learning, in addressing these difficulties. The study identified key research gaps, proposed future directions, and emphasized the need for hybrid optimization techniques, lightweight machine learning models, and real-world implementations. The findings contribute to the development of robust, scalable VLC-NOMA systems for 6G applications.
Read MoreDoi: https://doi.org/10.54216/FPA.200104
Vol. 20 Issue. 1 PP. 34-54, (2025)
Business executives and scholars maintain that Artificial Intelligence (AI) is positioned alongside pivotal human inventions and advancements such as fire, electricity, and the incandescent light bulb. By harnessing AI technologies, academic institutions can augment pedagogical approaches, elevate the caliber of education, and furnish learners with novel avenues to cultivate their proficiencies and competencies. However, on the contrary, the implementation of AI in higher education has provoked deliberations regarding whether institutions ought to prohibit its utilization entirely or promote its integration to enhance educational outcomes. Nevertheless, despite the escalating acknowledgment of AI's importance in the educational sphere, there needs to be more thorough exploration concerning its adoption and comprehending its impacts. Data was collected from 300 respondents to fill this gap by building on the 'Unified Theory of Acceptance and Use of Technology' (UTAUT) model. We empirically contribute to the existing literature by clarifying the fundamental factors that affect the adoption of AI within higher education, in addition to scrutinizing the consequences of AI on knowledge acquisition. Moreover, we elucidate the moderating effects of workload and temporal limitations. The findings provide substantial insights relevant to the incorporation of AI for knowledge acquisition in higher education and are anticipated to provoke further scholarly discussion.
Read MoreDoi: https://doi.org/10.54216/FPA.200105
Vol. 20 Issue. 1 PP. 55-67, (2025)