Browsing by Author "Balogun M. O."

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    A Comparative Analysis of Complexity of C++ and Python Programming Languages Using Multi- Paradigm Complexity Metric (MCM)
    (International Journal of Science and Research (IJSR), 2018-10-26) Balogun M. O.; Sotonwa K. A.
    Software complexity metrics have used to quantifydifferent types of software properties such as cost, effort, time, maintainability, understanding and reliability. The existing metrics considered limited factors that affect software complexity, but do not consider the characteristics that affect complexity of multi-paradigm languages. In this work, a Multi-paradigm Complexity Metric (MCM) for measuring software complexity was developed for multi-paradigm codes. Multi-paradigm languages that were considered in thiswork are C++ and Python, these two languages combine the features of procedural and object oriented paradigms, therefore this research began with investigation of factors that affect the complexity of procedural code and object oriented code, so that the developed metric could be used not only for procedural code, but also either object oriented codes or in more general for multi-paradigm codes. The developed metric was then applied on sample programs written in most popular programming languages such as Python and C++, and the result of the developed metric was further evaluated with other existing complexity metrics like effective line of code (eLOC), cyclomatic complexity metric and Halstead complexity measures. The study showed that the developed complexity metric have significant comparison with the existing complexity metrics and can be used to rank numerous programs and difficulties of various modules.
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    A Complexity Metric for Multi-Paradigm Programming Languages
    (International Journal of Emerging Technology and Advanced Engineering, 2014-04-22) Olabiyisi S. O.; Omidiora E. O.; Balogun M. O.
    Software complexity metrics are used to measure variety of software properties such as cost, effort, time, maintenance, understanding and reliability. Most of the existing metrics considered limited factors that affect software complexity, but do not consider the characteristics of multi-paradigm languages. In this work, a Multi-paradigm Complexity Metric (MCM) for measuring software complexity was developed for multi-paradigm codes. Multi-paradigm languages that were used in this work combine the features of procedural and object oriented paradigms, therefore this research began with investigation of factors that affect the complexity of procedural code, thereafter with a more modern approach, the research was further extended by adding object oriented features, so that the developed metric could be used not only for procedural code, but also either object oriented codes or in more general meaning for multi-paradigm codes. The developed metric was then applied on sample programs written in most popular programming languages such as Python, Java and C++, and was further evaluated with other existing complexity metrics like effective line of code (eLOC), cyclomatic complexity metric and Halstead complexity measures. The study showed that the developed complexity metric have significant comparison with the existing complexity metrics and can be used to rank competitive programs and difficulties of various modules.
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    Code Quality Metric of Searching Algorithms for Multi-Paradigm Languages
    (International Journal of Scientific Research and Management (IJSRM), 2019-05-20) Sotonwa K. A.; Balogun M. O.; Olusi Titilayo
    This study investigated the comprehensibility of a software code from a developer‟s point of view and proposed new metric accordingly. The factors that affect the complexity of procedural, object-oriented, and multi-paradigm codes were analyzed for this purpose. Addition to the investigated factors, various metrics and several aspects were combined in the proposed metric. The proposed metric were empirically validated in different paradigms.
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    Optimizing Support Vector Machine with Polynomial Kernel for Credit Card Fraud Detection
    (FUOYE Journal of Pure and Applied Sciences, 2023-10-01) Odeniyi L. A.; Oduntan E. O.; Balogun M. O.; Ogunrinde M. A.; Omoniyi V.
    The rate at which fraud relating to credit cards is increasing is alarming and requires accurate detection to curb its regular occurrence. Discovery of such fraud, especially in the financial world is still a challenge despite several research using various machine learning algorithms. Though SVM has proved its efficiency in producing good detection parameters, there is still a need to improve the accuracy for optimal results. Hence, a Polynomial Kernel optimization method of Support Vector Machine (SVM) was adopted to identify Credit Card Fraud. The data set used for this work was acquired from Kaggle and it presents transactions that occurred in two days with 492 frauds out of 284,807 transactions. The dataset was trained, tested and a parameter tuning using a polynomial kernel was performed, after which the performance of the model was evaluated. SVM was optimized with Polynomial kernel, Sigmoid kernel and Radial Basis Function (RBF) kernel and it was realized that sigmoid gave an accuracy of 76%, RBF gave an accuracy of 94% while Polynomial gave an accuracy of 100%. Hence, the result proved that SVM optimized with a Polynomial kernel outperformed other optimization techniques for detecting credit card fraud.
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    QUALITATIVE COMPARISON OF WI-FI TO FEMTOCELL (HNB) FOR INDOOR WIRELESS DATA ACCESS
    (Zaria Journal of Electrical Engineering Technology, Department of Electrical Engineering, Ahmadu Bello University, Zaria – Nigeria, 2020-03-20) Ahmed O. M.; Adebowale Q. R.; Imam-Fulani Y. O.; Balogun M. O.; Ajani A. A.
    The increasing pressure on spectrum resources of cellular networks has prompted service providers to identify the use of femtocells and Wi-Fi as options for increasing network quality and capacity for indoor data access. This work seeks to make a qualitative comparison of Wi-Fi and femtocell for indoor data access in a Long-Term Evolution (LTE) heterogeneous network, identifying which network access technology serves better for indoor data delivery, using video streaming and Voice over Internet Protocol (VoIP) as services of interest. The performance evaluation was carried out experimentally by using a live Wi-Fi and a Femtocell access point connected via same backhaul. A user equipment with Quality of Service (QoS) parameters measurement capabilities was used to measure parameters of interests from both devices under same measurement conditions for in different indoor scenarios multiple times. We observed differences in the QoS experiences in different scenarios for the access technologies observed, Wi-Fi showed better performance in all of the categories of measurements.
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    Reliability Assessment of 33KV Feeder, (A Case Study of Transmission Company of Nigeria, Ganmo Work Centre.)
    (World Journal of Innovative Research (WJIR), 2019-10-20) Balogun M. O.; Ahmed M. O.; Ajani A. A.; Olaoye H.
    According to statistics, about 80% of the power interruptions result from power distribution system failure. Historical assessment and predictive methods are normally used to evaluate the reliability of a distribution network. Most utilities focus more on historical assessment rather than predictive methods. Hence, it is vital in design and development of distribution network to study and analyse the reliability. This research adopted methods involving analysis and evaluation of reliability of one of the Nigeria transmission station (Ganmo 33KV Ilorin) feeders to see how reliability could be improved in the distribution system by incorporating reliability analysis in the systematic planning approach so that optimum reliability is achieved. Analytical method such as Markov model and reliability indices of each feeder was evaluated, assessed and compared to see how risk of failure could be reduced. The reliability indices for the year 2016 and 2017 are being considered as the case study. The outages on the TCN Ganmo 33KV feeders was studied for 24 months on daily outage data collected from the station. Based on the result obtained from the data analysis illustrated with graphs, it was deduced that dedicated feeders such as KAM and UNILORIN have the highest reliability and more available compared to others residential feeders. This can be attributed to the level of their load demands. Generally, the feeders have least reliability during the period of May to October due to high vegetation and rainfall.