The aim of Turkish Journal of Mathematics and Computer Science (TJMCS) is to bring together research papers in different areas of applied and pure mathematics as well as applications of computer science and various areas of science and technology. The journal will also publish a limited number of proceedings of conferences. These proceedings will be fully refereed and adhere to the normal standards of the journal.
The Turkish Journal of Mathematics and Computer Science is a peer-reviewed, open-access journal that publishes original research and review articles in all areas of mathematics and computer sciences. Subject matters cover pure and applied mathematics, fuzzy theory, theoretical computer science, algorithms, scientific computing, artificial intelligence, use and application of mathematics and mathematical knowledge in natural science, engineering, medicine and the social sciences.
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Coverage includes (Mathematics) |
Coverage includes (Computer Science) |
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· Algebra |
· Algorithm |
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· Algebraic Geometry |
· Artificial Intelligence |
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· Category Theory |
· Bioinformatics |
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· Complex Analysis |
· Computational Complexity |
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· Control Theory and Optimization |
· Computer Architecture |
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· Differential Equations |
· Computer Graphics |
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· Differential Geometry |
· Computer Network and Internet |
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· Discrete Mathematics |
· Database Systems |
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· Dynamical Systems and Ergodic Theory |
· Dependable Computing |
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· Functional Analysis |
· Distributed Computing |
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· Geometry |
· Formal Methods |
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· Mathematical Logic and Foundations |
· Grid Computing |
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· Mathematical Physics |
· High-Performance Computing |
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· Number Theory |
· Human-Computer Interaction |
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· Numerical Analysis |
· Image Processing |
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· Operator Theory |
· Information Security |
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· Probability Theory and Statistics |
· Knowledge-Based Systems |
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· Real Analysis |
· Natural Language Processing |
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· Topology |
· New Computational Models |
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· Pattern Recognition |
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· Software Engineering |
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· VLSI Design and Test |
Instructions for Authors
The style of the article should be concise. The first page of the manuscript should contain the title of the article, author’s name, current postal and e-mail addresses, and an informative abstract which should not exceed 100 characters. The main body of the manuscript should include the abstract which should be a summary of the entire paper. The abstract should be followed by a list of not more than six keywords, two to six classification codes from the Mathematics Subject Classification Scheme. Furthermore, the text should be divided into numbered sections with appropriate subheadings. Figures and tables should be incorporated into the text. References should be listed in alphabetical order according to the (first) author’s surname, be numbered and referred in the text by the same number in square brackets.
Manuscript submitted to this journal should:
It is necessary to submit a pdf file of the manuscript. The manuscript will be written in LaTeX typesetting system. The TJMCS (Turk. J. Math. Comput. Sci.) style file can be downloaded from the following link.
Publication Ethics and Publication Malpractice Statement
For all parties involved in the act of publishing (the author, the journal editor(s), the peer reviewer and the publisher), it is necessary to agree upon standards of expected ethical behavior. Any kind of unethical behavior is unacceptable, and TJMCS will not tolerate plagiarism in any form. Authors submitting articles to TJMCS affirm that manuscript contents are original. Authors must ensure that they have entirely written original work. By submitting a manuscript, the authors agree that the copyright for their article is transferred to the publisher when the article is accepted for publication. Furthermore, they warrant that their article has neither been published elsewhere nor it is under review for publication anywhere.
Authors' Ethical Responsibilities can be summarized as below:
1. The work submitted for publication must have not been published in another magazine or submitted at the same time.
2. Author (s) are required to make use of and/or quote in a complete and accurate way in order to benefit from other studies or to use other studies. The author (s) must have evidence that they have the necessary permissions for the use rights of the data used, research/measurement tools/analyzes.
3. The author (s) has an obligation to communicate with the editor in informing, correcting or withdrawing the journal editor or publisher if he/she finds a mistake or error related to his / her early published or evaluation work.
Review of Manuscripts
The editor must ensure that each manuscript is initially evaluated by the editor for originality. After passing this check, the manuscript is forwarded to two reviewers for single-blind peer review, each of whom will make a recommendation to accept, reject, or modify the manuscript. If both reviewers accept/(reject) the manuscript, it is “accept/(reject)”. In case, the editor received different recommendations from the reviewers, the manuscript is sent to a third reviewer.
Referees' Ethical Responsibilities are given below:
1. Admit only to evaluate the work related to the field of expertise.
2. Assessment should be done objectively only with respect to the content of the work.
3. The evaluation should be carried out on time and on the above ethical responsibility.
Publishing articles in the journal of TJMCS, downloading and reading of articles is free of charge, and also no article processing and publishing charges.
Bayram Şahin was born in Malatya, Turkey. He received his Bachelor’s degree from Ege University, İzmir, Turkey, in 1993 and his Ph.D from Inonu University in 2000. After graduating, Dr. Şahin worked as a post-doctoral fellow at University of Windsor from March 2003 to September 2003 and a research scholar from June 2007 to September 2007. He has led several TUBITAK funded projects at the interface of manifold theory and maps and he has written (or co-authored) eighty-one academic papers. He is the author of the monograph “Differential Geometry of Lightlike Submanifolds” (2010) , Riemannian Submersions, Riemannian Maps in Hermitian Geometry and Their Applications (2017),and the editors of Turkish Journal of Mathematics, Turkic World Mathematical Society (TWMS) Journal of Pure and Applied Mathematics and Mediterranean Journal of Mathematics. He is the recipient of Masatoshi Gunduz Ikeda research award at 2006. He is now a professor of Mathematics at Ege University, Turkey.
Area of expertise: Applied Mathematics
Faculty/Department: Natural and Agricultural Sciences, Institute of Groundwater Studies
ACADEMIC QUALIFICATIONS
BSc/MSc: Applied Mathematics, Azerbaijan State University (now Baku State University), Baku, Azerbaijan, 1983.
PhD: Mathematics (Differential Equation), Institute of Mathematics and Mechanics of Azerbaijan National Academy of Sciences (ANAS), Baku, Azerbaijan, 2002.
DSc: Information Technology (System Analysis, Control and Information Processing), Institute of Cybernetics (now Institute of Control Systems) of ANAS, Baku, Azerbaijan, 2010.
RECOGNITION/AWARDS
In 2020-2023 Ramiz Aliguliyev has been recognized among the world’s top 2% scientists in the field of artificial intelligence identified by Stanford University.
In 2017 he was elected corresponding member of ANAS in Informatics.
In 2014 he was awarded with “Taraggi” medal by the order of the President of the Republic of Azerbaijan.
In 2013 under the framework of the “ICT year” in the “3rd ICT Contest Competition” held by the Science Development Foundation under the President of the Republic of Azerbaijan jointly with the Ministry of Communications and Information Technologies, his article was awarded the 1st place for the best scientific work published in ICT field.
PROFESSIONAL QUALIFICATIONS
From 1983 to 1987 he worked as an engineer at the Institute of Cybernetics (now Institute of Control Systems) of Azerbaijan Academy of Sciences (AAS), Baku, Azerbaijan.
From 1988 to 2002 he worked as a leading engineer and a researcher at the Institute of Mathematics and Mechanics of AAS, Baku, Azerbaijan.
Since 2003 he is a head of department at the Institute of Information Technology of ANAS, Baku, Azerbaijan.
Since 2023 he is a director of the Institute of Cybersecurity and Artificial Intelligence at Azerbaijan Technical University, Baku, Azerbaijan
He has supervised 3 PhDs and 5 Masters, currently supervising 8 PhD students.
RESEARCH INTERESTS
Data Mining
Text Mining
Big Data Analytics
Machine Learning
Deep Learning
Scientometrics
Social Network Synthesis and Analysis
E-government Analysis
Artificial Intelligence
Evolutionary and Swarm Intelligence Algorithms
EDITORIAL, REVIEW and EXPERTISE ACTIVITY
Editorial Board Member of the journals:
Problems of Information Technology
CAAI Transactions on Intelligence Technology
TWMS Journal of Pure and Applied Mathematics
International Journal of Decision Support System Technology
Problems of Information Society
Informatics and Control Problems
International Journal of Sensors, Wireless Communications and Control
Turkish Journal of Mathematics & Computer Science
Communications
Artificial Intelligence Evolution
Ukrainian Journal of Information Systems and Data Science
He is a reviewer a lot of journals and conferences.
He has been a member of the program/organizing committees of more than 30 international and local conferences.
He is a member of the dissertation council at the Institute of Information Technology.
ACADEMIC NETWORKING
Google Scholar: https://scholar.google.com/citations?hl=en&user=cV0HqdgAAAAJ&view_op=list_works&sortby=pubdate
Scopus ( ID: 35561067300): https://www.scopus.com/authid/detail.uri?authorId=35561067300
ORCID : https://orcid.org/0000-0001-9795-1694
Web of Science (ResearcherID: A-1072-2013): https://www.webofscience.com/wos/author/record/1189983
ResearchGate: https://www.researchgate.net/profile/Ramiz-Aliguliyev
SELECTED PUBLICATIONS
R.Alguliyev, Ramiz Aliguliyev, & L.Sukhostat, “An approach for assessing the functional vulnerabilities criticality of CPS components”, Cyber Security and Applications, vol.3, 100058, 2025. https://doi.org/10.1016/j.csa.2024.100058 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & L.Sukhostat, “Radon transform based malware classification in cyber-physical system using deep learning”, Results in Control and Optimization, vol.14, 100382, 2024. https://doi.org/10.1016/j.rico.2024.100382 (WoS)
A.Bagirov, Ramiz Aliguliyev, & N.Sultanova, “Finding compact and well-separated clusters: Clustering using silhouette coefficients”, Pattern Recognition, vol.135, 109144, 2023. https://doi.org/10.1016/j.patcog.2022.109144 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & R.Alakbarov, “Constrained k-means algorithm for resource allocation in mobile cloudlets”, Kybernetika, vol.59, no.1, pp.88-109, 2023. https://doi.org/10.1016/10.14736/kyb-2023-1-0088 (WoS)
R.Alguliyev, Ramiz Aliguliyev, Y.Imamverdiyev, & L.Sukhostat, “History matching of petroleum reservoirs using deep neural networks”, Intelligent Systems with Applications, vol.16, 200128, 2022. https://doi.org/10.1016/j.iswa.2022.200128 (WoS)
Ramiz Aliguliyev & N.Adigozalova, “h-type indices for multiple authorship papers based on “relative first author” principle”, COLLNET Journal of Scientometrics and Information Management, vol.16, no.2, pp.305-330, 2022. https://doi.org/10.1080/09737766.2022.2098875 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & L.Sukhostat, “Parallel batch k-means for Big data clustering”, Computers & Industrial Engineering, vol.152, 107023, 2021. https://doi.org/10.1016/j.cie.2020.107023 (WoS)
R.Alguliyev, Y.Imamverdiyev, R.Mahmudov, & Ramiz Aliguliyev, “Information security as a national security component”, Information Security Journal, vol.30, no.1, pp.1-18, 2021. https://doi.org/10.1016/10.1080/19393555.2020.1795323 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & L.Sukhostat, “Weighted consensus clustering and its application to big data”, Expert Systems with Applications, vol.150, 113294, 2020. https://doi.org/10.1016/j.eswa.2020.113294 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & L.Sukhostat, “Efficient algorithm for big data clustering on single machine”, CAAI Transactions on Intelligence Technology, vol.5, no.1, pp.9-14, 2020. https://doi.org/10.1049/trit.2019.0048 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & F Yusifov, “Modified fuzzy TOPSIS+TFNs ranking model for candidate selection using the qualifying criteria”, Soft Computing, vol.24, no.1, pp.681-695, 2020. https://doi.org/10.1007/s00500-019-04521-2 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & F.Abdullayeva, “Multidisciplinary study of the problems of big data technologies in the oil and gas industry”, International Journal of Oil Gas and Coal Technology, vol.23, no.1, pp.92-105, 2020. https://doi.org/10.1504/IJOGCT.2020.104975 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & F.Abdullayeva, “Privacy-preserving deep learning algorithm for big personal data analysis”, Journal of Industrial Information Integration, vol.15, pp.1-14, 2019. https://doi.org/10.1016/j.jii.2019.07.002 (WoS)
R.Alguliyev, Ramiz Aliguliyev, N.Isazade, A.Abdi, & N.Idris, “COSUM: text summarization based on clustering and optimization”, Expert Systems, vol.36, no.1, e12340, 2019. https://doi.org/10.1111/exsy.12340 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & G.Niftaliyeva, “A method for social network extraction from e-government”, International Journal of Information Systems in the Service Sector, vol.11, no.3, pp.37-55, 2019. https://doi.org/10.4018/IJISSS.2019070103 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & F.Abdullayeva, “The Improved LSTM and CNN models for DDoS attacks prediction in social media”, International Journal of Cyber Warfare and Terrorism, vol.9, no.1, pp.1-18, 2019. https://doi.org/10.4018/IJCWT.2019010101 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & F.Yusifov, “MCDM for candidate selection in e-voting”, International Journal of Public Administration in the Digital Age, vol.6, no.2, pp.35-48, 2019. https://doi.org/10.4018/IJPADA.2019040103 (WoS)
A.Abdi, S.Shamsuddin, & Ramiz Aliguliyev, “QMOS: query-based multi-documents opinion-oriented summarization”, Information Processing & Management, vol.54, no.2, pp.318-338, 2018. https://doi.org/10.1016/j.ipm.2017.12.002 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & G.Niftaliyeva, “Filtration of terrorism-related texts in the e-government environment”, International Journal of Cyber Warfare and Terrorism, vol.8, no.4, pp.35-48, 2018. https://doi.org/10.4018/IJCWT.2018100103 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & N.Adigozalova, “Journal Impact Factor weighted by SJR and 5-year IF indicators of citing sources”, Journal of Scientometric Research, vol.7, no.2, pp.94-106, 2018. https://doi.org/10.5530/jscires.7.2.15 (WoS)
A.Abdi, N.Idris, R.Alguliev, & Ramiz Aliguliyev, ”Bibliometric Analysis of IP&M Journal (1980-2015)”, Journal of Scientometric Research, vol.7, no.1, pp.54-62, 2018. https://doi.org/10.5530/jscires.7.1.8 (WoS)
R.Muhamedyev, Ramiz Aliguliyev, Z.Shokishalov, R.Mustakayev, “New bibliometric indicators for prospectivity estimation of research fields”, Annals of Library and Information Studies, vol.65, no.1, pp.62-69, 2018. https://doi.org/10.56042/alis.v65i1.18656 (WoS)
A.Abdi, S.Shamsuddin, N.Idris, R.Alguliyev, & Ramiz Aliguliyev, “A linguistic treatment for automatic external plagiarism detection”, Knowledge-Based Systems, vol.135, pp.135-146, 2017. https://doi.org/10.1016/j.knosys.2017.08.008 (WoS)
A.Abdi, N.Idris, R.Alguliev, & Ramiz Aliguliyev, “Query-based multi-documents summarization using linguistic knowledge and content word expansion”, Soft Computing, vol.21, pp.1785-1801, 2017. https://doi.org/10.1007/s00500-015-1881-4 (WoS)
R.Alguliyev & Ramiz Aliguliyev, “Modifications to the journal impact factor”, COLLNET Journal of Scientometrics and Information Management, vol.11, no.1, pp.25-43, 2017. https://doi.org/10.1080/09737766.2016.1235251 (WoS)
A.Abdi, N.Idris, R.Alguliev, & Ramiz Aliguliyev, “An automated summarization assessment algorithm for identifying summarizing strategies”, PLoS ONE, vol.11, no.1, e0145809, 2016. https://doi.org/10.1371/journal.pone.0145809 (WoS)
A.Abdi, N.Idris, R.Alguliev, & Ramiz Aliguliyev, “PDLK: Plagiarism detection using linguistic knowledge”, Expert Systems with Applications, vol.42, no.22, pp.8936-8946, 2015. https://doi.org/10.1016/j.eswa.2015.07.048 (WoS)
A.Abdi, N.Idris, R.Alguliev, & Ramiz Aliguliyev, “Automatic summarization assessment through a combination of semantic and syntactic information for intelligent educational systems”, Information Processing & Management, vol.51, no.4, pp.340-358, 2015. https://doi.org/10.1016/j.ipm.2015.02.001 (WoS)
R.Alguliyev, Ramiz Aliguliyev, & N.Isazade, “An unsupervised approach to generating generic summaries of documents”, Applied Soft Computing, vol.34, pp.236-250, 2015. https://doi.org/10.1016/j.asoc.2015.04.050 (WoS)
R.Alguliev, Ramiz Aliguliyev, T.Fataliyev, & R.Hasanova, “Weighted consensus index for assessment of the scientific performance of researchers”, COLLNET Journal of Scientometrics and Information Management, vol.8, no.2, 2014. https://doi.org/10.1080/09737766.2014.954864 (WoS)
R.Alguliev, Ramiz Aliguliyev, & N.Isazade, “Multiple documents summarization based on evolutionary optimization algorithm”, Expert Systems with Applications, vol.40, no.5, pp.1675-1689, 2013. https://doi.org/10.1016/j.eswa.2012.09.014 (WoS)
R.Alguliev, Ramiz Aliguliyev, & C.Mehdiyev, “An optimization approach to automatic generic document summarization”, Computational Intelligence, vol.29, no.1, pp.129-155, 2013. https://doi.org/10.1111/j.1467-8640.2012.00437.x (WoS)
R.Alguliev, Ramiz Aliguliyev, & N.Isazade, “MR&MR-Sum: maximum relevance and minimum redundancy document summarization model”, International Journal of Information Technology and Decision Making, vol.12, no.3, pp.361-393, 2013. https://doi.org/10.1142/S0219622013500156 (WoS)
R.Alguliev, Ramiz Aliguliyev, & N.Isazade, “CDDS: Constraint-driven document summarization models”, Expert Systems with Applications, vol.40, no.2, pp.458-465, 2013. https://doi.org/10.1016/j.eswa.2012.07.049 (WoS)
R.Alguliev, Ramiz Aliguliyev, & N.Isazade, “Formulation of document summarization as a 0-1 nonlinear programming problem”, Computers & Industrial Engineering, vol.64, no.1, pp.94-102, 2013. https://doi.org/10.1016/j.cie.2012.09.005 (WoS)
R.Alguliev, Ramiz Aliguliyev, & N.Isazade, “DESAMC+DocSum: differential evolution with self-adaptive mutation and crossover parameters for multi-document summarization”, Knowledge-Based Systems, vol.36, pp.21-38, 2012. https://doi.org/10.1016/j.knosys.2012.05.017 (WoS)
R.Alguliev, Ramiz Aliguliyev, & M.Hajirahimova, “GenDocSum+MCLR: Generic document summarization based on maximum coverage and less redundancy”, Expert Systems with Applications, vol.39, no.16, pp.12460-12473, 2012. https://doi.org/10.1016/j.eswa.2012.04.067 (WoS)
R.Alguliev, Ramiz Aliguliyev, M.Hajirahimova, & C.Mehdiyev, “MCMR: Maximum coverage and minimum redundant text summarization model”, Expert Systems with Applications, vol.38, no.12, pp. 14514-14522, 2011. https://doi.org/10.1016/j.eswa.2011.05.033 (WoS)
R.Alguliev, Ramiz Aliguliyev, & F.Ganjaliyev, “Investigation the role of similarity measure and ranking algorithm in mining social network”, Journal of Information Science, vol.37, no.3, pp. 229-234, 2011. https://doi.org/10.1177/01655515114009 (WoS)
R.Alguliev, Ramiz Aliguliyev, & C.Mehdiyev, “Sentence selection for generic document summarization using an adaptive differential evolution algorithm”, Swarm and Evolutionary Computation, vol.1, no.4, pp.213-222, 2011. https://doi.org/10.1016/j.swevo.2011.06.006 (WoS)
R.Alguliev, Ramiz Aliguliyev, & C.Mehdiyev, “pSum-SaDE: a modified p-median problem and self-adaptive differential evolution algorithm for text summarization”, Applied Computational Intelligence and Soft Computing, Article 351498, 2011. https://doi.org/10.1155/2011/351498 (WoS)
R.Alguliev, Ramiz Aliguliyev, & S.Nazirova, “Classification of textual e-mail spam using data mining techniques”, Applied Computational Intelligence and Soft Computing, Article 416308, 2011. https://doi.org/10.1155/2011/416308 (WoS)
Ramiz Aliguliyev, “Clustering techniques and discrete particle swarm optimization algorithm for multi-document summarization”, Computational Intelligence, vol.26, no.4, pp.420-448, 2010. https://doi.org/10.1111/j.1467-8640.2010.00365.x (WoS)
Ramiz Aliguliyev, “Clustering of document collection – A weighting approach”, Expert Systems with Applications, vol.36, no.4, pp.7904-7916, 2009. https://doi.org/10.1016/j.eswa.2008.11.017 (WoS)
Ramiz Aliguliyev, “Performance evaluation of density-based clustering methods”, Information Sciences, vol.179, no.20, pp.3583-3602, 2009. https://doi.org/10.1016/j.ins.2009.06.012 (WoS)
Ramiz Aliguliyev, “A new sentence similarity measure and sentence based extractive technique for automatic text summarization”, Expert Systems with Applications, vol.36, no.4, pp.7764-7772, 2009. https://doi.org/10.1016/j.eswa.2008.11.022 (WoS)
R.Alguliyev & Ramiz Aliguliyev, “Automatic text documents summarization through sentences clustering”, Journal of Automation and Information Sciences, vol.40, no.9, pp.53-63, 2008. https://doi.org/10.1615/JAutomatInfScien.v40.i9.50 (WoS)
R.Alguliyev & Ramiz Aliguliyev, “Experimental investigating the F-measure as similarity measure for automatic text summarization”, Applied and Computational Mathematics, vol.6, no.2, pp.278-287, 2007. http://www.acmij.az/view.php?lang=az&menu=journal&id=257 (WoS)
GRANTS
He was project manager/participant of the
6 grants supported by Azerbaijan Science Foundation
and
5 grants supported by Science Fund of the State Oil Company of the Azerbaijan Republic.
Prof. Dr. Nurettin DOĞAN, after completing his primary and secondary education in Ankara, graduated from Ankara University, Department of Mathematics. He completed his master's and doctoral studies at Ankara University. He worked at Gazi University Technical Education Faculty Electronics and Computer Education Department and Gazi University Faculty of Technology Computer Engineering Department. He is currently working at Selcuk University, Faculty of Technology, Department of Computer Engineering. He has studies on approximate analytical series solution methods of dynamical systems. His current research interests are related to image encryption applications.
2004 yılında Doğu Akdeniz Üniversitesi'nden bilgisayar mühendisliği alanında lisans derecesi ve 2007 ve 2013 yıllarında sırasıyla Gazi Üniversitesi, Ankara, Türkiye'den bilgisayar mühendisliği alanında yüksek lisans derecesi ve elektrik-elektronik eğitimi alanında doktora derecesi aldı. 2021 yılında doçentlik ünvanı aldı. Araştırma ilgi alanları arasında kablosuz sensör ağları, enerji optimizasyonu, Nesnelerin İnterneti, derin öğrenme, doğal dil işleme ve akıllı şehir yer almaktadır.