Browsing by Author "Babatunde, Akinbowale Nathaniel"
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Item Design and Implementation of Ayo Olopon Game(2015) Babatunde, Akinbowale Nathaniel; Abikoye, Oluwakemi Christiana; Mabayoje, Medinat Abolore; Akintola, Abimbola Ganiyat; Oderemi, ChristianaThe difficulty encountered with the present manual mode of the “Ayo olopon” game is majorly on the tools used in playing it. The game utilizes the earth as the board of the game and uses stones, leaves as other parameters in playing it. Though some still use boards carved from wood and seeds but there is still a problem with portability. This research which is centred on automating the “Ayo olopon” game is inevitable because of the increasing need for system automation. There are many difficulties associated with the existing manual approach of playing the “Ayo olopon” game which ranges from loss or misplacing of seeds to inaccuracy in scores calculation due to human errors. This system is designed to efficiently handle the entire process of the game play. Two algorithms were implemented for the game manipulation. The first for handling the incrementing of the next cell while the other an entire play turn. Out of the diverse rules for the game play, one was selected and implemented. With the proposed system, “Ayo olopon” game playing is more efficient when compared to its present mode of play. The study outlined the concepts of the analysis and design methodology of the proposed system, compares it with the existing system and explains the design and implementation of the system using Microsoft C# as its programming language on the Visual Studio.NET platform serving as the Integrated Development Environment (IDE). The research was tested using the Windows operating system and worked successfulItem Handwritten Character Recognition using Brainnet Library(Faculty of Computers and Applied Computer Science, "Tibiscus" University of Timişoara, Romania., 2016) Babatunde, Akinbowale Nathaniel; Abikoye, Oluwakemi Christiana; Babatunde, Ronke Seyi; Kawu, R.OHandwriting has continued to persist as a means of communication and recording information in dayto- day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition of handwriting has practical significance, as in reading handwritten notes in a PDA, in postal addresses on envelopes, in amounts in bank checks, in handwritten fields in forms, etc. An off-line handwritten alphabetical character recognition system using multilayer feed forward neural network is described, and a method, called, diagonal based feature extraction is used for extracting the features of the handwritten alphabets. This project implements this methodology using BrainNet Library. Ten data sets, each containing 26 alphabets written by various people, are used for training the neural network and 130 different handwritten alphabetical characters are used for testing. The proposed recognition system performs quite well yielding higher levels of recognition accuracy compared to the systems employing the conventional horizontal and vertical methods of feature extraction. This system, if modified will be suitable for converting handwritten documents into structural text form and recognizing handwritten namesItem Hybridized Intrusion Detection System Using Genetic and Tabu Search Algorithm(Faculty of Computers and Applied Computer Science, "Tibiscus" University of Timişoara, Romania., 2017) Abikoye, Oluwakemi Christiana; Aro, Taye Oladele; Obisesan, Racheal Oyeranti; Babatunde, Akinbowale NathanielAs transactions, data communication and information systems are drastically increasing in the society, so many people are connected through internet for e-commerce and other electronic activities. The introduction of internet technology in business brings about great relief in reaching the end users. Also this technology invites numerous security threats of misuses and intrusions. Intrusion detection systems are significant element for network security infrastructure which plays key role in the detection of several attacks along the network. They are several techniques being employed in intrusion detection, but these methods are not completely flawless. In quest for an efficient Intrusion Detection System (IDS), this study employs hybridization technique which involves the Genetic Algorithm and Tabu-search to produce a robust Intrusion Detection System. Evaluation of the system on KKD 99 intrusion database, shows that the performance of proposed hybridized IDS is better than that of Genetic algorithm or tabu search method alone which can significantly detect almost all anomaly data in the computer network.Item An Improved Palm Vein Based Recognition System(The International Journal of Computing & ICT research, Makerere University. Makerere., 2016) Abikoye; Chukwu, M; Babatunde, Akinbowale NathanielThough biometrics techniques has been recording high level of security when compared with other forms of authentication, it still come with challenges of speed and accuracy of the technique been used. In this paper an improved palm vein based recognition system was developed and implemented. The development procedure was divided into four stages which are Image enhancement, Image segmentation, Image thinning and Pattern Matching. The Image was enhanced using Histogram Equalization, after which it was passed for Segmentation by K-Means algorithm. The binarized image from K-Means was then thinned using the Zhang Suen’s algorithm. The Pattern Matching section of the project was done using the Euclidean Distance. Inter-distances of the intersections from the thinned image were stored in a database for subsequent matching. Results from the various test carried out showed that the system has high speed and accuracyItem A K-means and fuzzy logic-based system for clinical diagnosis (staging) of cervical cancer(Inderscience, 2017) Abikoye, Oluwakemi Christiana; Olajide, Emmanuel Oluwaseun; Babatunde, Akinbowale Nathaniel; Akintola, Abimbola GaniyatIn cases of the burden arising from cancer world, cervical cancer is the most common type of gynaecological cancer, accounting 8% (527,624 cases in 2012) of all female malignancies, second only to breast and colorectal cancer. Women with cervical cancer constitute patient populations that are in need of ongoing, person-centred supportive care. The unavailability of technologies that can determine the stage of cervical cancer constitutes a problem in the actual diagnosis. Previously physician predict the cancer stage on the basis of their experience in the field, however this is prone to error because man’s judgement are sometimes clouded by emotions. This research seeks to address this problem with the design of a k-means and fuzzy logic based system for clinical diagnosis (staging) of cervical cancer. The K-means algorithm was used for the grouping of data and fuzzy logic for the rule based prognosis of cervical cancerItem Survey of Video Encryption Algorithms(Covenant University, 2017) Babatunde, Akinbowale Nathaniel; Jimoh, Rasheed Gbenga; Abikoye, Oluwakemi Christiana; Isiaka, BResearch on security of digital video transmission and storage has been gaining attention from researchers in recent times because of its usage in various applications and transmission of sensitive information through the internet. This is as a result of the swift development in efficient video compression techniques and internet technologies. Encryption which is the widely used technique in securing video communication and storage secures video data in compressed formats. This paper presents a survey of some existing video encryption techniques with an explanation on the concept of video compression. The review which also explored the performance metrics used in the evaluation and comparison of the performance of video encryption algorithms is being believed to give readers a quick summary of some of the available encryption techniques.