Browsing by Author "Balogun, Monsurat O"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Enhancing Human Identification Systems Through Bi-modal Fusion Using Negative Selection Algorithm
    (COVENANT JOURNAL OF ENGINEERING TECHNOLOGY, 2024-02-27) Balogun, Monsurat O; Jimada-Ojuolape, Bilkisu; Odeniyi, Latifat A
    The Negative Selection Algorithm (NSA) is a computational technique inspired by the human immune system and widely used in various fields like intrusion detection, network security, data mining, and pattern recognition. However, its effectiveness in human identification has not been thoroughly explored. This study focuses on utilizing NSA for human image classification, specifically in a bi-modal system combining physiological traits (faces and fingerprints) and behavioral traits (signatures and voices), as well as a uni-modal system using all features. The research collected 2400 images from 200 individuals, pre-processed images, and salient features selected for easy classification. NSA was used for image classification in both bi-modal and uni-modal systems. The results demonstrated NSA's effectiveness, particularly in the bi-modal system. The biometric system that fused behavioral traits exhibited high accuracy, with true positive and true negative rates of 141% and 144%, respectively, and an overall accuracy of 95%. The system is based solely on physiological traits and achieved slightly lower accuracy rates at 89%. Furthermore, among the uni-modal systems, the voice-based system stood out with a true positive rate of 131% and an accuracy of 88.33%. These findings emphasize the advantages of combining different biometric traits, showcasing the potential for increased accuracy in identification systems. The study highlights NSA's role in enhancing classification accuracy, suggesting the developed biometric systems could significantly improve the performance and reliability of various integrated identification systems.
  • Thumbnail Image
    Item
    Feasibility of Wind Energy Utilization for Sustainable Power Generation in Ilorin, Kwara State, Nigeria's North-Central Region
    (ABUAD Journal of Engineering Research and Development (AJERD), 2024-05-16) Balogun, Monsurat O; Jimada-Ojuolape, Bilkisu; Taiwo, James Ayo; Olusi, Titilayo
    The escalating energy demands across Nigeria, especially in remote rural areas, have outpaced the capacity of the national electricity grid, necessitating the development of independent and sustainable energy sources. Among the renewable options, wind energy stands out as a promising solution. This study focuses on assessing the potential of wind energy in Ilorin, located in Kwara State, within Nigeria's north-central region. Utilizing data collected from 2007 to 2021 by the Nigerian Meteorological Agency, the research examines monthly average wind speeds at two specific coordinates in Ilorin, considering variations in air density. The study utilizes a 15-year set of monthly average wind velocities obtained from the Nigerian Meteorological Agency (NiMet) Headquarters in Abuja, measured at a height of 10 meters above ground level. By employing the 2-coefficient Weibull statistical model and extrapolation principles across different altitudes ranging from 150 to 900 meters above ground level, the study reveals distinct seasonal patterns of wind speeds ranging from 1.1 to 5.1 m/s in Ilorin. Furthermore, wind power density values ranging from 6.7 to 39.20 W/m2 are identified, with optimal wind attributes observed at altitudes exceeding 900 meters. These findings provide valuable insights for assessing the feasibility of wind energy utilization and designing efficient systems in Nigeria's north-central regions, aiding in the sustainable energy transition.