SUAD Institutional Repository
by SUAD Library

Your reference for the Sorbonne University Abu Dhabi research output and research impact

 
Research outputs
645
Disciplines
9
Researchers
95
Recent Additions
  • Publication
    The Rise of Techonological risks in Banking
    (2021)
    Alnuaimi, Aisha
    The thesis explored the question of the potential rise in technological risks within the banking industry. It sought to examine the accelerated uptake of advanced technological solutions and the subsequent influence of the accompanying technological risks on banks during the COVID-19 pandemic era. Being an extensive research area, the study uses Abu Dhabi Islamic Bank (ADIB), located in the United Arab Emirates (UAE), as a case study. A qualitative research design comprising survey questionnaires and interviews were used to collect data from 30 participants from a population of ADIB employees in different departments. The survey questions and interviews asked closed-ended and open-ended questions to determine the participants' opinions concerning technological advancement and risks in the banking industry. The results indicate that ADIB scaled up its online operations during the pandemic using advanced technologies. Secondly, the findings confirm that the accelerated technological advancements caused an increase in technological risks. Four main technological risks were identified: risk to data confidentiality, data loss, impaired systems, and cyber-attacks. Lastly, according to the findings, the frequency of cyber-attacks, such as hacking and phishing, increased. As a result, the IT department had to deal with increased employee complaints about technical difficulties.
      2
  • Publication
    The Regulation of Green Finance
    (2021)
    Abhilasha
  • Publication
    Knowledge Fusion by Harnessing Support Vector Machines for Collaborative Uncertain Data Classification in Multiagent Systems
    (2024)
    Hussein, Ahmad MohdAziz
    ;
    Al-azzeh, Rashed M H
    ;
    Mughaid, Ala
    ;
    ;
    Migdady, Hazem
    ;
    Abualigah, Laith
    Distributed data mining (DDM) has emerged as a useful method for analyzing data that is spread across multiple sources. Nevertheless, DDM has other challenges that restrict its effectiveness, such as autonomy, privacy, efficiency, and implementation. DDM's rigidity and lack of adaptability may render it unsuitable for numerous applications due to its requirement for a consistent environment, administration, control, and categorization procedures. In order to address these challenges, we suggest the implementation of MAS-DDM, which combines a multiagent system (MAS) with DDM. MAS, or Multiagent Systems, is a methodology used to create independent agents that possess shared environments and can collaborate and communicate with one another. The study showcases the advantages and attractiveness of MAS-DDM. In the context of MAS-DDM, agents can exchange their thoughts, even when the data they possess is classified and cannot be disclosed. Other agents can then decide whether to incorporate these beliefs into their decision-making process, which may result in a revision of their initial assumptions about each data class. MAS-DDM focuses on the support vector machine (SVM) method, which is commonly employed for handling uncertain data. Our investigation demonstrates that the performance of MAS-DDM surpasses that of DDM strategies that do not incorporate communicative processes, even when all MAS-DDM agents utilize the same methodology. We present empirical evidence demonstrating that the precision of the categorization job is significantly enhanced through the exchange of knowledge among agents.
      3  1
  • Publication
    Economic evaluation for influenza
    (2019)
    A. Al Tamimi