Browsing by Author "Adeniyi, J. K."

Now showing 1 - 3 of 3
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    Diagmal: A Malaria Coactive Neuro-Fuzzy Expert System
    (Computational Science and Its Applications – ICCSA 2020, 2020) Oladele, Tinuke Omolewa; Ogundokun, R. O.; Awotunde, J. B.; Adebiyi, M. O.; Adeniyi, J. K.
    In the process of clarifying whether a patient or patients is suffering from a disease or not, diagnosis plays a significant role. The procedure is quite slow and cumbersome, and some patients may not be able to pursue the final test results and diagnosis. The method in this paper comprises many fact-finding and data-mining methods. Artificial Intelligence techniques such as Neural Networks and Fuzzy Logic were fussed together in emerging the Coactive Neuro-Fuzzy Expert System diagnostic tool. The authors conducted oral interviews with the medical practitioners whose knowledge were captured into the knowledge based of the Fuzzy Expert System. Neuro-Fuzzy expert system diagnostic software was implemented with Microsoft Visual C# (C Sharp) programming language and Microsoft SQL Server 2012 to manage the database. Questionnaires were administered to the patients and filled by the medical practitioners on behalf of the patients to capture the prevailing symptoms. The study demonstrated the practical application of neuro-fuzzy method in diagnosis of malaria. The hybrid learning rule has greatly enhanced the proposed system performance when compared with existing systems where only the back-propagation learning rule were used for implementation. It was concluded that the diagnostic expert system developed is as accurate as that of the medical experts in decision making. DIAGMAL is hereby recommended to medical practitioners as a diagnostic tool for malaria.
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    Hand geometry recognition: an approach for closed and separated fingers
    (International Journal of Electrical and Computer Engineering (IJECE), 2022) Adeniyi, J. K.; Oladele, Tinuke Omolewa; Akande, O. N.; Adeniyi, T. T.
    Hand geometry has been a biometric trait that has attracted attention from several researchers. This stems from the fact that it is less intrusive and could be captured without contact with the acquisition device. Its application ranges from forensic examination to basic authentication use. However, restrictions in hand placement have proven to be one of its challenges. Users are either instructed to keep their fingers separate or closed during capture. Hence, this paper presents an approach to hand geometry using finger measurements that considers both closed and separate fingers. The system starts by cropping out the finger section of the hand and then resizing the cropped fingers. 20 distances were extracted from each finger in both separate and closed finger images. A comparison was made between Manhattan distance and Euclidean distance for features extraction. The support vector machine (SVM) was used for classification. The result showed a better result for Euclidean distance with a false acceptance ratio (FAR) of 0.6 and a false rejection ratio (FRR) of 1.2.
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    A Joint Neuro-fuzzy Malaria Diagnosis System
    (Journal of Physics: Conference Series, 2021) Oladele, Tinuke Omolewa; Ogundokun, R. O.; Misra, S.; Adeniyi, J. K.; Jaglan, V.
    Diagnosis takes a definitive role in the course of determining about clarifying patients as either having or not having the disorder. This method is relatively sluggish and tedious. Various fact-finding and data-mining methods are part of the approach of this article. In the development of the Collaborative Neuro-Fuzzy Expert System diagnosis platform, Neural Networks and Fuzzy Logic, which are artificial intelligence methods, have been merged together. Oral interviews were conducted with medical professionals whose experience was caught in the Expertise Developed Fuzzy Proficient Scheme. With Microsoft Visual C # (C Sharp) Programming Language and Microsoft SQL (Structured Query Language) Server 2012 to handle the database, the Neuro-Fuzzy Expert Framework diagnostic software was introduced. To capture the predominant signs, questionnaires were administered to the patients and filled out by the doctors on behalf of the patients.