Papers by Anthony O N A O L A P O Olabode
IJARCET, 2019
Multimodal system is capable of increasing the scope and variety of input information the system ... more Multimodal system is capable of increasing the scope and variety of input information the system takes from the users for authentication. However, Face, Ear and fingerprint have compatibility formation but little research have been done in the area of comparing biometric features in order to determine their overall accuracy in multimodal systems. A total of 2160 datasets were used for this experiment. 1260 datasets were used for the training and 900 were used for testing. These images were preprocessed using histogram equalization and feature extraction was carried out using Principal component analysis (PCA). Self-organizing feature map (SOFM) and back propagation neural network (BPNN) was used for classification. The performance of the developed multimodal biometric systems (face, ear and finger) was compared and evaluated in MATLAB environment. The results showed that SOFM has high recognition accuracy and time than BPNN.
ANNALS, 2019
The efficiency with which searching is carried out often has significant impact on the overall ef... more The efficiency with which searching is carried out often has significant impact on the overall efficiency of a program. Some of the factors affecting the performance of informed tree based or heuristic search algorithms include high exponential execution time to search, drastic memory or storage usage and number of nodes visited. However, prioritizing each of these factors based on their influence has been a major challenge. Therefore, this research prioritized computational time, memory usage and number of nodes visited based on their influence using factor analysis by principal component.
Annals, 2019
Mobile Agents (MA) are objects that migrate through the nodes of heterogenous networks to perform... more Mobile Agents (MA) are objects that migrate through the nodes of heterogenous networks to perform intelligent path finding tasks. Prioritizing the metaheuristics algorithms (PSO, ACO, GA and SA) with the best performance in terms of cost value and computational time efficiency for mobile agents path planning has been a major challenge. The performance of these selected meteheuristic algorithms was evaluated. Prototypes of mobile agents were introduced into two dimensional (2-D) workspace of adhoc network consisting of 16 nodes. The PSO, ACO, GA and SA were introduced into the mobile workspace for path planning and encoding. The corresponding path plans from PSO, ACO, GA and SA were later used for finding path and implemented in MATLAB environment. The performance of the metaheuristic techniques was evaluated using Computational Time (CT), Cost Value (CV), Program Effort (PE) and Program Size (PS).
IJSER, 2019
Blind algorithm is a type of algorithm that uses no information about the likely direction leadin... more Blind algorithm is a type of algorithm that uses no information about the likely direction leading to the goal state. There exist some factors affecting the performance of blind algorithms which includes high execution time, low memory usage and number of nodes. This paper critically evaluated and prioritized these factors based on their influence on the performance of blind algorithms. Five blind algorithms (Breadth first, Depth-first, Iterative deepening, Bidirectional and Uniform cost) were selected for this research. These algorithms were implemented in C# programming language. Experiments were conducted on these algorithms by varying the input route lines of Arik airlines as case study to generate data. Factor analysis by principal component was used for the evaluation and validation of the most critical factor. The result proved that number of nodes was the main factor affecting blind algorithms.
LAUTECH Journal of Engineering and Technology , 2017
The efficiency with which searching is carried out often has significant impact on the overall ef... more The efficiency with which searching is carried out often has significant impact on the overall efficiency of a program. There are factors affecting the efficiency of informed tree based search algorithms which includes high exponential execution time, drastic memory or storage usage and number of nodes visited. This paper critically evaluates the level at which each of these factors affect the efficiency of informed tree based search algorithms. Four informed tree based search algorithms (best first, A*, greedy and hill climbing) were studied and implemented in Java. Experiments were performed on the four algorithms by varying the input routes line of Romania road map distance to generate data. Factor analysis by principal component was used for the analysis of the generated data. The performance of each of the algorithm was evaluated using number of nodes, memory usage and time taken. The study revealed that main factor affecting the efficiency of informed tree based algorithm was time taken.
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Papers by Anthony O N A O L A P O Olabode