Browsing by Author "Jilantikiri, L. J."

Now showing 1 - 4 of 4
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    APPLICATION OF SUPPORT VECTOR REGRESSION MODELLING FOR THE PREDICTION OF IMPACT ATTENUATION OF 3D PRINTED HIP PROTECTORS
    (Faculty of Engineering and Technology, University of Ilorin, 2023-06) Suleiman Abimbola, Yahaya; Muniru, I.O.; Saminu, Sani; Ibitoye, M.O.; Ajibola, T.M.; Jilantikiri, L. J.; Ripin, Z.M.; Ridzwan, M.I.Z.
    3D printed thermoplastic polyurethanes of different shore hardness were used to make hip protectors for the prevention of osteoporotic hip fracture, which was then tested. The result was used to develop a support vector regression model to estimate the effect of the protector shore hardness, shell thickness, and infill density on the impact attenuation capacity at different energy levels. The results from the model show that the impact attenuation ability of a hip protector is significantly dependent on the infill density of the hip protector and its shore hardness. Excellent agreement was found between the model results and test results.
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    DESIGN OF A LEUKEMIA DETECTION SYSTEM USING DIGITAL BLOOD SMEAR IMAGES
    (Faculty of Engineering and Technology, University of Ilorin, 2023-06) Saminu, Sani; Muniru, I.O.; Suleiman Abimbola, Yahaya; Oladimeji, A. J.; Ajibola, T.M.; Ibitoye, M.O.; Ahmed, Yusuf Kola; Jilantikiri, L. J.
    Leukaemia is a fatal blood cancer that occurs due to the formation of abnormal and excessive increases in white blood cells in the bone marrow or blood. The traditional approaches used to diagnose the disease involve the manual analysis of blood sample images obtained from a microscope. This approach is tedious, slow, timeconsuming, and prone to errors. Therefore, automatic detection of leukaemia based on the counting of the two blood cells is paramount for diagnosis and increasing the patient’s survival rate. This paper presents a system that can detect each of the two blood cells needed through image processing, segmentation, and classification. The detection, classification, and counts are only limited to two of the cells present in the digital blood smear which are the white blood cells (WBCs) and red blood cells (RBCs). The model was evaluated with a collection of confirmed cases and normal cases to test its effectiveness in predicting the presence of Leukaemia by computing the ratio of WBC to RBC. The suggested model exhibits good performance results and can be utilized to make a reliable computer-aided diagnosis detection of leukaemia cancer.
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    Development of an automated healthcare record management system
    (Faculty of Engineering, Adeleke University, Ede, Nigeria, 2019) Yahaya, Suleiman Abimbola; Jilantikiri, L. J.; Hassan, K. A; Akande, K. A; Yahaya, A
    This project focused on improving mobility for a blind person by creating an obstacle and pit detecting walking stick using ultrasonic sensors. The project comprised of both hardware and software. The hardware consists of ultrasonic sensors, buzzers and a microcontroller, while the software consists of Arduino Integrated Development Environment (Arduino IDE), which was used to program the microcontroller. A Polyvinyl Chloride (PVC) casing was used to house the hardware components. The ultrasonic sensor that detects obstacles was programmed to detect obstacles at a distance of 100 cm or below and causes the buzzer to sound so as to alert the blind person. Another ultrasonic sensor was programmed to identify pit at a depression of 18 cm and above. This stick was tested to detect obstacles by 80 different blindfolded individuals within a room with different objects placed at different positions. Results showed that the percentage reduction of collision rate when comparing the developed ultrasonic walking stick to a normal white cane is 90.1%. This shows that the ultrasonic walking stick is reliable for domestic use by a blind person.
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    Development of obstacle and pit detecting ultrasonic walking stick for the blind.
    (Faculty of Engineering, Federal University Oye-Ekiti, Nigeria., 2019) Yahaya, S. A.; Jilantikiri, L. J.; Oyinloye, G. S.; Zaccheus, E. J.; Ajiboye, J.O; Akande, K.A.
    This project focused on improving mobility for a blind person by creating an obstacle and pit detecting walking stick using ultrasonic sensors. The project comprised of both hardware and software. The hardware consists of ultrasonic sensors, buzzers and a microcontroller, while the software consists of Arduino Integrated Development Environment (Arduino IDE), which was used to program the microcontroller. A Polyvinyl Chloride (PVC) casing was used to house the hardware components. The ultrasonic sensor that detects obstacles was programmed to detect obstacles at a distance of 100 cm or below and causes the buzzer to sound so as to alert the blind person. Another ultrasonic sensor was programmed to identify pit at a depression of 18 cm and above. This stick was tested to detect obstacles by 80 different blindfolded individuals within a room with different objects placed at different positions. Results showed that the percentage reduction of collision rate when comparing the developed ultrasonic walking stick to a normal white cane is 90.1%. This shows that the ultrasonic walking stick is reliable for domestic use by a blind person.