Dr. Abdul Nasir
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Academic Career Length
6Years (2021-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Journal Article
NJNaeem Jan
Naeem JanAbdul NasirMAMohsin S. Alhilal
Mohsin S. AlhilalSKSami Ullah Khan
Sami Ullah Khan
Dragan PamucarAAAbdulrahman Alothaim
Abdulrahman AlothaimRecently, there has been enormous development due to advancements in technology. Industries and enterprises are moving towards a digital system, and the oil and gas industries are no exception. There are several threats and risks in digital systems, which are controlled through cyber-security. For the first time in the theory of fuzzy sets, this research analyzes the relationships between cyber-security and cyber-crimes in the oil and gas sectors. The novel concepts of complex intuitionistic fuzzy relations (CIFRs) are introduced. Moreover, the types of CIFRs are defined and their properties are discussed. In addition, an application is presented that uses the Hasse diagram to make a decision regarding the most suitable cyber-security techniques to implement in an industry. Furthermore, the omnipotence of the proposed methods is explained by a comparative study.
Journal Article
Abdul NasirNJNaeem Jan
Naeem JanAGAbdu H. Gumaei
Abdu H. GumaeiSKSami Ullah Khan
Sami Ullah KhanFAFahad Albogamy
Fahad AlbogamyTechnology is rapidly advancing and every aspect of life is being digitalized. Since technology has made life much better and easier, so organizations, such as businesses, industries, companies and educational institutes, etc., are using it. Despite the many benefits of technology, several risks and serious threats, called cyberattacks, are associated with it. The method of neutralizing these cyberattacks is known as cybersecurity. Sometimes, there are uncertainties in recognizing a cyberattack and nullifying its effects using righteous cybersecurity. For that reason, this article introduces interval-valued complex intuitionistic fuzzy relations (IVCIFRs). For the first time in the theory of fuzzy sets, we investigated the relationships among different types of cybersecurity and the sources of cyberattacks. Moreover, the Hasse diagram for the interval-valued complex intuitionistic partial order set and relation is defined. The concepts of the Hasse diagram are used to inspect different cybersecurity techniques and practices. Then, using the properties of Hasse diagrams, the most beneficial technique is identified. Furthermore, the best possible selection of types of cybersecurity is made after putting some restrictions on the selection. Lastly, the advantages of the proposed methods are illuminated through comparison tests.
19 January 2022 in Journal of Function Spaces
Journal Article
NJNaeem Jan
Naeem Jan
RMRabia Maqsood
Rabia Maqsood
Abdul NasirMAMohsin S. Alhilal
Mohsin S. Alhilal
AAAmerah Alabrah
Amerah AlabrahNANaziha Al-Aidroos
Naziha Al-AidroosMany industries are developing robust models, capable of analyzing huge and complex data by using machine learning (ML) while delivering faster and more accurate results on vast scales. ML is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. ML tools enable organizations to swiftly identify profitable opportunities and potential risks. Besides these uses, ML also has a wide range of applications in our daily lives. So, the development in ML is most important in this age of digital system to solve more complex problems. In order to further develop ML and diminish the uncertainties to improve accuracy, an innovative concept of complex bipolar intuitionistic fuzzy sets (CBIFSs) is introduced in this article. Further, the Cartesian product of two CBIFSs is defined. Moreover, the complex bipolar intuitionistic fuzzy relations (CBIFRs) and their types with suitable examples are defined. In addition, some important results and properties are also presented. The proposed modeling techniques are used to study different ML factors and their interrelationship, so that the functionality of ML might be enhanced. Furthermore, the advantages and benefits of proposed methods are described by their side to side comparison with preexisting frameworks in the literature.
31 March 2023 in Expert Systems with Applications
Journal Article
Abdul NasirNJNaeem Jan
Naeem JanDragan PamucarSKSami Ullah Khan
Sami Ullah Khan
8 June 2021 in Security and Communication Networks
Journal Article
NJNaeem Jan
Naeem JanSRSaif Ur Rehman
Saif Ur RehmanAbdul NasirHAHassen Aydi
Hassen AydiSKSami Ullah Khan
Sami Ullah Khan17 February 2022 in Scientific Programming
Journal Article
NJNaeem Jan
Naeem JanBABushra Akram
Bushra Akram
Abdul NasirMAMohsin S. Alhilal
Mohsin S. Alhilal
AAAmerah Alabrah
Amerah AlabrahNANaziha Al-Aidroos
Naziha Al-AidroosArtificial intelligence (AI) has made the life more efficient and powered many programs and services. AI is progressing rapidly, and the future is arriving faster than the predictions. Soon, AI will be more proficient as compared to humans in all aspects. Many industries are using AI for the analysis of data to find the best methods for investments. In this article, we developed the impacts of AI on different industries through the new concepts of complex bipolar picture fuzzy set (CBPFS) proposed in the current study. The CBPFS has an extensive structure that includes membership, abstinence, and nonmembership degrees with the ability to deal with multivariable problems. These degrees are fuzzy numbers between 0 and 1 inclusive; 0 being the lowest and 1 being the highest value for each degree, which reflect different meaning for membership, nonmembership, and abstinence. Furthermore, the paper explains the Cartesian product between CBPFSs and complex bipolar picture fuzzy relation (CBPFR) and its types with suitable example. Furthermore, through a comparison test with preexisting fuzzy set frameworks, some benefits of CBPFS are presented in this article.
About Me
Abdul Nasir is a Lecturer and PhD Scholar in the Department of Mathematics at Gomal University, Dera Ismail Khan, Pakistan. He received his BS and MPhil degrees in Mathematics from Gomal University and was awarded a Gold Medal for outstanding academic performance. He has authored and co-authored more than 20 research articles in internationally recognized journals and has actively contributed to the advancement of fuzzy mathematics and its interdisciplinary applications.
His research interests include fuzzy set theory, fuzzy relations, fuzzy graph theory, uncertainty modeling, intelligent decision-making systems, artificial intelligence, machine learning, computer vision, cybersecurity, information technology, operations research, supply chain management, pattern recognition, image processing, medical diagnosis, and big data analytics. His research focuses on developing novel mathematical frameworks and computational models for addressing uncertainty and solving complex real-world problems.
Dr. Nasir serves as a reviewer for several international journals and actively collaborates with researchers from diverse disciplines. His current research is directed toward the integration of advanced fuzzy methodologies with emerging technologies to support intelligent systems, data-driven decision-making, and innovative solutions for scientific and industrial challenges.