Computer Science -Scholarly Publications
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- ItemOpen AccessCommunication of Scientists through Scientific Publications: Math-Net.Ru as a Case Study.(CEUR Workshop Proceedings, 2020-09) Pechnikov, Andrey; Chebukov, Dmitry; Nwohiri, AnthonyWe present a study of two scientific collaboration graphs built using data drawn from Math-Net.Ru, an all-Russian mathematical portal. One of the graphs is a citation-based scientific collaboration graph. It is an oriented graph with no loops and multiple edges. Its vertices denote authors of papers, while the arcs connecting these vertices denote that the first author has, in at least one of his papers, cited the work of the second author. The second graph is a coauthor- ship-based graph. It is a non-oriented graph, where the vertices denote authors, while edges connecting two vertices indicates that the two authors have coauthored at least a paper. We conduct a traditional study of the main characteristics of both graphs, such as degrees of vertices, influence of vertices, diameter, mean distance, connected components and clustering. Both graphs are found to have a similar connectivity structure – both have a giant component and several small components. Using the two graphs, we split the set of Math-Net.Ru authors. In this set, it was revealed that more than 40% of authors who have co-authored a paper with someone have not ever cited their co-authors. This means there is no deliberate plan to cite each other’s work in the journals registered in Math-Net.Ru.
- ItemOpen AccessOn Some Journal Citation Properties: Math-Net.Ru as a Case.(CEUR Workshop Proceedings, 2021-09-20) Pechnikov, Andrey; Chebukov, Dmitry; Nwohiri, AnthonyThis paper presents a study of bibliographical references cited in articles published by Math- Net.Ru journals. Based on data obtained from mathematical portal Math-Net.Ru, we built a journals citation graph, with its vertices denoting journals, and edges representing bibliographical references (citations) between papers published in these journals. To increase the reliability of the constructed graph, we chose a 2010-2021 citation time interval, when distribution of citing papers (papers that have cited other works) had stabilized at 3500-4500 citations per year. The structure of citation ageing is investigated; it is shown that the half-life of these citations is 8 years. So, the publication date of cited papers (papers that have been cited by other works) was limited to the year 2002. The constructed citation graph was found to have a small diameter and high density, indicating that there is a high level of research collaboration in Math-Net.Ru. It is shown that there is no Matthew effect as a pronounced advantage in the citations of leading journals in relation to less well-known ones. The adequacy of the Math-Net.Ru journal citation graph as a scientific collaboration model is confirmed by comparing the ranking of journals included the citation graph with their Science Index ranking in scientific electronic library eLIBRARY.RU. The two rankings were found to have a direct moderate relationship between themselves. A number of substantive conclusions are drawn from analysis of the citation graph.
- ItemOpen AccessReview of Fraud Detection Methods and Development of a Data Mining Technique for Real-Time Financial Fraud Detection.(Bayero University Kano, 2022) Ogude, Ufuoma; Nwohiri, Anthony; Ugbaja, GeraldineFraud that involves cell phones, insurance claims, tax return claims, credit card transactions, government procurement etc. represent significant problems for governments and businesses. Technology advances have brought along new opportunities and security challenges. Due to the dramatic increase in fraud which has cost businesses billions of dollars each year, several modern fraud detection techniques are continually evolving to meet the unprecedented challenge. Data mining (DM) is the most recognized and effective technology that has been deployed for fraud detection. This study looks at the concept of DM and current techniques used in detecting fraud and reviews DM methods used to detect fraudulent payment transactions. It explores some of the most effective DM techniques for detecting different types of fraud, categorizing them based on supervised and unsupervised methods. An efficient model that can differentiate fraudulent transactions from genuine transactions based on a given dataset is proposed.
- ItemOpen AccessAI-Powered Plagiarism Detection: Leveraging Forensic Linguistics And Natural Language Processing(FUDMA Journal of Sciences, 2021) Nwohiri, Anthony; Joda, Opemipo; Ajayi, OlasupoPlagiarism of material from the Internet is nothing new to academia and it is particularly rampant. This challenge can range from borrowing a particularly apt phrase without attribution, to paraphrasing someone else’s original idea without citation, to wholesale contract cheating. Plagiarized content can infringe on copyright laws and could incur hefty fines on publishers and authors. Unintentional plagiarism mostly occurs due to inaccurate citation. Most plagiarism checkers ignore this fact. Moreover, plagiarizers are increasingly becoming negatively “smarter”. All these necessitate a plagiarism detector that would efficiently handle the challenges. Several plagiarism detectors have been developed but each with its own peculiar limitations. This paper aims at developing an AI-driven plagiarism detector that can crawl the web to index articles and documents, generate similarity score between two local documents, train users on how to properly format in-text citations, identify source code plagiarism and use natural language processing and forensic linguistics to properly analyse plagiarism index.
- ItemOpen AccessHybrid of RSA Cryptography with Huffman Compression Algorithms as a Data Security Measure for Internet Users(Covenant University, 2016-06) Oladeji, F. A.; Ajetunmobi, R. A.; Ajayi, O. O.; Adebayo, A.; Olatunji, M.Security of transmitted data calls for serious concern especially in this informationcentric era where data resources of businesses and organization are held on remote servers. Too much dependence on the network to protect data had exposed the data to danger of cybercrimes and middlemen attacks. It is then expedient that the stakeholders concerned with the data are involved in the security process that is, users are involved in placing some security measures on their data before giving it to the cloud or remote storages offering data storage as a service. Data encryption and compression algorithms play dependable roles on security of transmitted data (Forouzan and Fegan, 2006; Comer, 2009). Encryption disguises the content of a document such that only the sender and the receiver can get it back. There are many data encryption algorithms ranging from data encryption standard (DES), advanced encryption standard (AES) to Rivest-Shamir- Adleman (RSA) algorithms (Comer, 2009). Data compression or encoding on its own reduces the size of the data before it is transmitted. Data compression has the advantages of reducing network traffic by reducing the size of data to be transmitted. Data encoding algorithms also exist with differences in the technique and type of data to be coded. Among them are Huffman, Lempel-Ziv and arithmetic encoding mechanisms to mention a few. The two steps are not compelled to be adopted on all data or across networks. Firewall sometimes prompts the alert that this data is not encrypted. This work suggests a hybrid of encryption and data compression algorithms as a combined effort from the user Level. The showcased algorithms are the use of RSA cryptosystem and Huffman encoding scheme. Data meant for transmission is first encrypted by the human (source of the data) and then subjected to encoding before submission. The implementation was carried out using Java language and sample GUI-based screenshots were documented.