Excellence in Artificial Intelligence Award
Ola Khresat is a researcher affiliated with Zarqa University, Jordan, whose supplied academic profile identifies Cybersecurity as the subject area. The provided research references cover organizational internal control, financial reporting standards, and machine-learning-based fault detection in industrial Internet of Things (IoT) environments. These topics highlight the importance of information integrity, intelligent data analysis, and reliable digital systems. The application of machine learning to industrial monitoring demonstrates the relevance of artificial intelligence to identifying operational abnormalities and supporting intelligent technological solutions. [1] [2] [3]
Abstract
This article presents the academic research profile of Ola Khresat, affiliated with Zarqa University, Jordan, with Cybersecurity identified as the subject area. Artificial Intelligence is an interdisciplinary field that combines machine learning, computational methods, data analysis, and automated reasoning to develop intelligent solutions for complex problems. Its applications include cybersecurity, industrial monitoring, information management, and automated fault detection. The supplied Scopus profile reports 23 documents, 25 citations, and an h-index of 3.[1] [2] [3]
Keywords
Machine Learning; Industrial Internet of Things; IoT Fault Detection; Intelligent Monitoring; Information Security; Data Integrity; COSO Framework; Internal Control; IFRS 15; Financial Reporting; Time-Series Analysis; Industrial Monitoring.
Introduction
Artificial Intelligence has become an important area of technological development, enabling computers and digital systems to perform tasks involving data analysis, pattern recognition, prediction, and automated decision-making. Through machine learning, computational modelling, and intelligent algorithms, AI supports applications across industries, including finance, healthcare, telecommunications, manufacturing, and cybersecurity. Cybersecurity focuses on protecting digital information, networks, applications, and connected infrastructure against unauthorized access, disruption, and malicious activities. [1] [2] [3]
Research Profile
Ola Khresat is affiliated with Zarqa University in Jordan. The supplied academic information identifies Cybersecurity as the subject area and provides a Scopus author identifier and Google Scholar profile for academic reference. According to the supplied Scopus information, the research profile includes 23 documents, 25 citations, and an h-index of 3. These bibliometric indicators provide a quantitative overview of the publication and citation information provided for the researcher. Such indicators may change over time as additional research is published, indexed, and cited. [1] [2] [3]
Research Contributions
Artificial Intelligence and Cybersecurity contribute to the development of reliable digital environments through intelligent data analysis, automated monitoring, and computational approaches to identifying potential problems. Machine learning provides methods for examining large datasets, recognizing patterns, and supporting predictions. These approaches can be applied to industrial monitoring, network security, information management, and operational risk analysis. The supplied publications offer context for understanding the research themes associated with organizational integrity, financial information, and intelligent fault detection. [1] [2] [3]
Publications
The following three references were supplied for this academic profile. Their publication titles and source links are reproduced as provided. The works address internal control components based on the COSO framework, IFRS 15 and telecommunications profitability, and machine-learning-based fault detection in industrial IoT monitoring.
Research Impact
Research involving artificial intelligence, cybersecurity, and intelligent industrial monitoring can contribute to the development of reliable and efficient digital systems. Machine-learning-based fault detection offers methods for analysing industrial data, identifying abnormal patterns, and supporting timely maintenance decisions. These approaches can help improve operational awareness and reduce the challenges associated with monitoring complex connected infrastructure.[1] [2] [3]
Award Suitability
The Excellence in Artificial Intelligence Award recognizes academic and research contributions that demonstrate innovation, technical knowledge, and meaningful applications of intelligent computational methods.Ola Khresat’s supplied academic profile identifies Zarqa University, Jordan, as the institutional affiliation and Cybersecurity as the subject area. The provided Scopus information includes 23 documents, 25 citations, and an h-index of 3. [1] [2] [3]
Conclusion
Ola Khresat’s academic profile is associated with Zarqa University, Jordan, and the research subject of Cybersecurity. The supplied Scopus information reports 23 documents, 25 citations, and an h-index of 3.These research themes provide context for the relationship between artificial intelligence, intelligent data analysis, organizational integrity, and dependable digital systems. The Scopus and Google Scholar profiles provide additional researcher identification resources for academic reference. [1] [2] [3]
External Links
References
- The Efficiency of Applying the Internal Control Components Based on COSO Framework to Transparently Carry out Tasks and Services, Ensure Integrity and Enhance Quality and Efficiency: Case Study – The Greater Amman Municipality.
https://ideas.repec.org/a/jfr/ijfr11/v11y2020i2p371-381.html
- Impact of the Application of IFRS 15 on the Profitability of Jordanian Telecom Companies (Case Study: Jordan Orange Telecom).
https://ideas.repec.org/a/jfr/ijfr11/v12y2021i2p308-317.html
- Identification of Fault Detection in IoT using Machine Learning: The Framework for Analysis of Time-Series based Industrial Monitoring.
https://ieeexplore.ieee.org/abstract/document/11325700