Browsing by Author "Ajiboye, Johnson Adegbenga"

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A Comparison of Code Maintainability in Agile Environment
(IUP Journal of Information Technology, 2016-06-01) Mary Adebola Ajiboye; Matthew Sunday Abolarin; Ajiboye, Johnson Adegbenga
The demand for quick delivery of quality software is becoming high among software clients due to the fast changing technology in the dynamic world. Agile software development meets this demand and has gained appropriate and wide acceptance among software practitioners. However, the quality of such software is greatly impacted by its maintainability. Unfortunately, existing works focused only on the flexibility aspect of maintainability without paying attention to timely delivery. In this work, maintainability as a function of time to correct codes was examined among various categories of software developers. Deliberate errors, ranging from two to nine, were introduced into sets of agile codes written in python programming language and given to 100 programmers, each in the groups of individual junior, individual expert, random, expert pairs, junior pairs and junior expert pairs. The results revealed that random pair programmers spent the highest time of 21.88 min/bug on the average, while individual experts spent the least time of 16.26 min/bug.
ANALYSIS OF SPECTRUM OCCUPANCY PREDICTION RESULTS FOR MAITAMA ABUJA
(International Conference on Communication and Information Science (ICCIS), 2024) Ajiboye, Johnson Adegbenga; Mary Adebola Ajiboye; Babatunde Araoye Adegboye; Daniel Jesupamilerin Ajiboye; Jonathan Gana Kolo; Abiodun Musa Aibinu
This research investigates the efficacy of Artificial Neural Networks (ANN) in predicting spectrum occupancy in Maitama, Abuja, Nigeria, focusing on frequency bands ranging from 30 MHz to 300 MHz. The primary objective was to evaluate the accuracy of ANN-based predictions of spectrum usage and compare these predictions with actual measurements. The study employed ANN to forecast spectrum occupancy across various frequency bands, and the predicted data were then compared with empirical measurements to assess the performance of the model. The analysis revealed that prediction errors were generally low across all frequency bands, with most errors falling below 1.5%. Specifically, the 30-47 MHz sub-band demonstrated an average percentage difference between the actual and predicted value of 0.087%, with a maximum error of 1.12% occurring at frequency of 44.65 MHz. For the 47.05-68 MHz band, the average percentage difference was slightly higher at 0.106%, and the maximum error was 2.18% occurring at frequency of 50.2 MHz. In the 68.05-74.8 MHz band, the average percentage error was 0.040%, but with highest error of 0.232% at frequency of 73.95 MHz. The 74.85-87.45 MHz band showed the most accurate predictions with an average error of just 0.010%, and a maximum error of 0.174% at 75.1 MHz. Overall, the highest prediction error was 0.106% in the 47.05-68 MHz band, whereas the lowest was 0.010% in the 74.85-87.45 MHz band. These results highlight the high accuracy of ANN in predicting spectrum usage, demonstrating its potential for effective spectrum management and planning in Maitama, Abuja.
Cognitive Radio Networks, a Key Technology of Future Wireless Communication: Challenges and Opportunities
(IUP Journal of Telecommunications, 2012-11-01) Ajiboye, Johnson Adegbenga; Yinusa Ademola Adediran
It is a well-known and established fact that the current approach of fixed spectrum allocation, the command-and-control model, makes the spectrum or the finite resource to be grossly underutilized or inefficient. There are so many bands of the spectrum already licensed to users but which in reality are unoccupied at some instance in time thereby creating spectrum holes. These are 'opportunities' that could be harnessed. Cognitive Radio (CR) is a promising technology being envisioned to solve the problem of spectrum underutilization and allows for real-time spectrum management. The CR, in a non-interference basis, opportunistically explores the unused channel, thereby ensuring efficient usage of this 'scarce' resource. The CR is a sure technology for the next generation wireless systems. In a CR, a licensed user, also called a Primary User (PU), has a priority over the Secondary User (SU) which has no spectrum license. Therefore, at the arrival of a PU, an opportunistic SU vacates the occupied channel and seeks another empty channel to be allocated. In this way, spectral efficiency is greatly enhanced. In this work, we examine the challenges that this new technology is bound to face.
Comparative Analysis of Macro Femto Networks Interference Mitigation Techniques
(IJWMT, 2022-12-20) Katfun Philemon Dawar; Abraham U. Usman; Bala Alhaji Salihu; Michael David; Supreme Ayewoh Okoh; Ajiboye, Johnson Adegbenga
When interference is reduced, the benefits of using a macrocell and femtocell heterogeneous network (Macro-Femto) heterogeneous network (HetNet) can be increased to their full potential. In this study, Enhanced Active Power Control (EAPC), Active Power Control (APC), and Power Control (PC1) interference mitigation strategies are applied, and their performances in uplink and downlink transmission of 5G Non-Stand-Alone (NSA) architecture are compared. According to the findings of a MATLAB simulation, the EAPC technique utilized a lower amount of transmit power for the Macro User Equipment (MUE), the Home User Equipment (HUE), and the femtocell logical node (Hen-gNB), in comparison to the APC and PC1 techniques. While PC1 approach required less en-gNB transmission power. The MUE, HUE, hen-gNB, and en-gNB throughput of the EAPC approach was much higher. This work will enable wireless system designers and network engineers know the appropriate technique to utilize to achieve desired Quality of Service (QoS) while conserving network resources
Design and Development of An IoT – Based Multi – Health Vital Signs Monitoring System
(I3C 2024, 2024-04-22) Adegboye N.J; Dauda U.S; Ajiboye, Johnson Adegbenga; Ohize H.O; Adegboye B.A
This study presents the design and development of an IoT-based multi-health vital signs monitoring system that can monitor a patient’s basic health physiological parameters in real-time. In this system, four (4) sensors were used to capture the data from the patient. These are body temperature sensor, electrocardiogram (ECG) sensor, accelerometer sensor and the eye blink sensor. The hardware modules were interfaced with the liquid crystal display (LCD) to display the required data. Memory modules stored the designated phone numbers. The GSM module retains connectivity with the cellular networks acting as SMS receiver, which sends data on the patient’s vital signs. The LCD displays the data, which can be seen through the IoT. The microcontroller was programmed using C++ programming language and connects all sensors. This enabled conveyance of data on the patient’s health condition via IoT to the doctor for further processing and analysis.
Design and Implementation of a 5 kVA Inverter
(IUP Journal of Electrical and Electronic Engineering, 2016-10-01) Ajiboye, Johnson Adegbenga; Chukwuka Anene; Mary Adebola Ajiboye; Abraham U. Usman
The paper describes the design and construction of a 5 kVA Pulse Width Modulated (PWM) Metal Oxide Semiconductor Field Effect Transistor (MOSFET)-based inverter, which works on the principle of PWM. The inverter uses IC SG3524 and a pair of Twelve MOSFETs to drive the load. The design and implementation starts with the power supply. Component selection was made with the aid of electronics data book, which made the design and calculations very easy. One main feature of this inverter is the monitoring section, and the battery-charging section connected to the inverter circuit. The inverter converts DC supply of the battery into AC power supply required by most electrical appliances/equipment when the AC main is not available; and when the AC main is available, the supply goes to the AC main sensor, the relays and battery charging section of the inverter. This inverter can be used for domestic purpose, and it is not recommended for industrial purpose where high current is required for application, such as starting a heavy-duty motor
Design and Implementation of Real Time Internet of Things (IoT) Enhanced Irrigation System
(El-Amin University Journal of Computing (EAUJC), 2024-04-01) J. A. Ojo; Ajiboye, Johnson Adegbenga; M. A. Ajiboye; D. J. Ajiboye; H. O. Ohize; A. A. Isa
Irrigation is a practice that has existed for a long time. Irrigation is the process of supplying water to the soil during drought or unfavourable weather conditions. Over the years, irrigation practices have evolved in order to eliminate the risk of manual irrigation. This risk includes over irrigation, under irrigation, erosion among others. Modern irrigation practices aim to reduce these problems by incorporating sensor technology, Internet of Things (IoT) and automations. The aim of this work is to design and a Real-Time IoT enhanced irrigation system which utilizes data about the condition of the environment to automate the irrigation process. This system makes use of soil moisture sensor, a rain sensor and a temperature and humidity sensor to capture real time environmental data and makes logic decisions based on the collected data. An ESP 32 microcontroller functions as the brain of the system by collecting data from the sensors and controlling the pump accordingly. The system also employs lot technology using Arduino Cloud loT platform in order to provide remote accessibility. The experimental evaluation involved subjecting the irrigation system to two distinct soil conditions; one dry and the other wet. The results demonstrate the functionality of the system: when rain sensor readings fall below the set threshold of 30% and soil moisture sensor readings drop below 15%, the irrigation pump is activated to compensate for the lack of rainfall and soil moisture. Furthermore, the system responds to environmental conditions, activating the pump for an extended period when relative humidity is below 60% and the temperature exceeds 25°C. Conversely, when the soil is already wet, indicated by high soil moisture sensor readings, the pump remains permanently turned off. This automated irrigation system showcases the potential to optimize water usage and enhance efficiency in response to dynamic environmental factors.
DEVELOPMENT OF AGILE PRODUCTIVITY METRICS OF INDIVIDUAL EXPERT JAVASCRIPT DEVELOPERS FOR SOFTWARE PROJECT MANAGERS
(Humminbird Publications and Research International, 2024-01-29) Abdulgafar A.; Makinde J.K; Ajiboye, Johnson Adegbenga; Ajiboye M.A
Software Project Managers require metrics to measure productivity in team work. Since agile software development require continuous improvement, metrics helps in identifying bottlenecks and inefficiencies thereby enabling teams to refine their processes iteratively. Productivity metrics also helps in effective resource allocation and optimization to ensure timely delivery of software products by Software Project Managers. Although metrics have been developed for traditional software programmers little work has been done in developing metrics for Agile Software Project Managers specifically for JavaScript Program. In this work, metrics for Individual Expert agile software programmers and specifically for JavaScript was developed. Programs in JavaScript was designed and developed to record the time spent in correcting deliberate errors introduced. Experiment was conducted among one hundred programmers' group of Individual Expert pairs with the aim of recording time spent in debugging the codes, The curve fit regression models of time spent in debugging a number of bugs in agile software written in JavaScript programming language for project managers revealed that Cubic model had the highest R squared value of 0.996 which is closely followed by the quadratic model with a value of 0.980 while the compound, growth and exponential models have the least value of 0.868.
DEVELOPMENT OF MODEL METRICS FOR INDIVIDUALS AND PAIR PROGRAMMERS AMONG SOFTWARE DEVELOPERS IN AN AGILE ENVIRONMENT
(2023) Ajiboye M.A; Ajiboye, Johnson Adegbenga; Audu W.M; Ajiboye D.J; Ohize H.O; Majin R.N; Abolarin M.S
In this work, maintainability as a function of time to correct codes was examined among various categories of software developers. Deliberate errors, ranging from two to ten, were introduced into sets of agile codes written in python programming language and given to 100 programmers each in the groups of Individual Junior, Individual Expert, Random, Expert pairs, junior pairs and Junior Expert pairs. The time spent to correct the errors was analysed using regression model for prediction. Bivariate correlation was used to check the relationships between the number of bugs in projects and the time spent to correct the errors. The correlation between the number of bugs and time of debugging was highly significant, strong and positive. This revealed that the time spent in correcting system software errors increased significantly as the number of bugs increased. Linear, logarithmic, inverse, quadratic, cubic and exponential regression models were used to generate metrics with time spent on error as dependent variable and number of bugs as independent variable for each of the pair and individual programmers. On the average, cubic model gave the highest R2 value of 0.639 in comparison to other models. Therefore, Cubic model gave the best fit as it explains the patterns of the relationship between the dependent and independent variable most appropriately.
DSP in Communication Engineering - A Review
(I3C 2024, 2024-04-22) Ajiboye, Johnson Adegbenga; Jiya Z.J; Paul M.; Ajiboye M.A; Ajiboye D.J; Majin R.N
This paper provides a comprehensive review of Digital Signal Processing (DSP) in communication engineering, elucidating its fundamental principles, practical applications, and recent advancements. Beginning with an overview of DSP's distinguishing features and historical evolution, the paper delineates its pivotal role in processing real-world signals, including speech, image, and seismic data. Furthermore, the introduction of Software Defined Radio (SDR) is examined, underscoring its transformative impact on communication systems by enabling dynamic spectrum access and multi-standard operation through DSP algorithms. Additionally, the emergence of Quantum Signal Processing is explored, highlighting its significance in secure communication through Quantum Key Distribution (QKD) and Quantum Error Correction. Despite the benefits offered by DSP, challenges such as computational complexity and signal distortions are addressed, emphasizing the need for advanced techniques and algorithms to mitigate these issues. Ultimately, this paper elucidates DSP's enduring relevance and innovation in shaping the future of communication engineering.
Dynamic Spectrum Access (DSA) in Wireless Cognitive Radio Networks (WCRN)
(2013-02-01) Ajiboye, Johnson Adegbenga; Yinusa Ademola Adediran; Mary Adebola Ajiboye
Dynamic Spectrum Access (DSA) is a technology that senses the unused 'free' but allocated portion of the radio frequency spectrum on a non-interfering basis. These unused bands are also known as 'holes' or 'white spaces'. DSA also refers to the time-varying, flexible usage of parts of the radio spectrum under consideration of regulatory and technical restrictions. This type of spectrum access is due to the dynamic behavior that the Secondary User (SU) must employ in order to access the spectrum, while avoiding interfering with a Primary User (PU). Intelligent or Cognitive Radio (CR) is a platform on which the DSA can be implemented. CRs are radio systems that autonomously coordinate the usage of spectrum. They utilize radio spectrum when it is not being used by incumbent (primary) radio systems. Underutilized spectrum can be exploited with the concepts of DSA and CR. This paper reviews the techniques that can be deployed for DSA reliably in a Wireless Cognitive Radio Network (WCRN) and models of network architecture-based DSA in Cognitive Radio Networks (CRN).
Generation of Random Numbers for Data Security Applications
(7th Annual Engineering Conference, 2006-06-28) Usman A.U; Ajiboye, Johnson Adegbenga
In this age of Electronic connectivity, the issue of data security is becoming more and more of great concern. The growth in computer systems and their interconnections via networks has increased the dependence of several organizations and individuals on information stored and communicated using these systems. Hence, there is need for data and resources to be well protected to guarantee its authenticity and to protect systems from network-based attacks. Cryptography and network security have matured, leading to the development of practical, readily available applications to enforce network security. This work covered a review of the concept of randomness with the stringent randomness requirement in data security systems giving particular attention to the Blum-Blum-Shub random number generator.
HYBRID AUTOREGRESSIVE NEURAL NETWORK (ARNN) MODEL FOR SPECTRUM OCCUPANCY PREDICTION
(NJEAS, 2022) Ajiboye, Johnson Adegbenga; Adegboye B.A; Aibinu A.M; Kolo J.G; Ajiboye M.A; Usman A.U
A secondary spectrum user cannot transmit in a channel before sensing and knowing the spectrum occupancy state as this may cause interference. This poses a major challenge because these operations ought to be performed in each time slot and thereby causing a substantial delay before the user gains access to the spectrum, leading to inefficient utilization. Therefore, a channel predictive system will mitigate this problem. In this work, an ensemble machine learning model for spectrum occupancy prediction was developed. The developed model was trained using a sample of Power Spectrum Density (PSD) data collected from the field for a period of twenty four hours within a frequency range of 30-300 MHz. The frequency range was grouped into sub bands. Based on the training data and the corresponding output data, the neural network model trains itself to come up with the best weights which can generally be used by the AR model for unseen data. After computing the weights, the performance was first tested on the entire training data, on the validation dataset and on the test dataset. Prediction results revealed an overall accuracy of 98.32% with band 4 (74.85-87.45 MHz) having the highest accuracy of 99.01% and the lowest accuracy of 89.39% in band 2 (47.05-68 MHz).
MANAGEMENT OF ELECTRIC POWER IN NIGERIA
(International Conference on Information Systems and Management Science, 2018) Ajiboye, Johnson Adegbenga; Mary Adebola Ajiboye; Misra Sanjay
One–Bit Compressive Sensing Algorithm for Wideband Spectrum Sensing: A Review
(I3C 2024, 2024-04-22) Majin R.N; Kolo J.G; Dauda U.S; Ajiboye, Johnson Adegbenga
Spectrum sensing (SS) is one of the most important techniques in wireless communication for understanding the radio environment. SS techniques, however, are ineffective since they require costly, impractical high-rate analog-to-digital converters (ADCs) for timely communications. However, there are challenges and limitations in traditional spectrum sensing techniques (SSTs), including estimation of sparsity level, selection of the number of measurements, noise uncertainty, receiver uncertainty, sensitivity at low signal-to-noise-ratio (SNR) values, and interference from channel coding. One-bit compression (CS) has been seen as a promising sensing technique that allows extremely easy, efficient, and fast sampling and quantization for wideband spectrum sensing. It can be used in cognitive radio (CR) communication by making use of sparsity in spectrum occupancy brought about by underutilization of the spectrum. In this paper, we provide an overview of compressive spectrum sensing (CSS) algorithms in wideband CR, the current state-of-the-art of CSS in wideband spectrum sensing (WBSS) communication, and its advantages and limitations.
Pair Programming – Cubic Prediction Model Results for Random Pairs and Individual Junior Programmers
(2023-11-06) Mary Adebola Ajiboye; Matthew Sunday Abolarin; Ajiboye, Johnson Adegbenga; Abraham Usman Usman; Sanjay Misra
Due to the rapidly evolving technology in the dynamic world, there is a growing desire among software clients for swift delivery of high quality software. Agile software development satisfies this need and has been widely and appropriately accepted by software professionals. The maintainability of such software, however, has a significant impact on its quality. Unfortunately, existing works neglected to consider timely delivery and instead concentrated primarily on the flexibility component of maintainability. This research looked at maintainability as a function of time to rectify codes among Individual Junior and Random pair soft ware developers. Data was acquired from an experiment performed on software developers in the agile environment and analyzed to develop the quality model metrics for maintainability which was used for prediction. One hundred programmers each received a set of agile codes created in the Python programming language, with deliberate bugs ranging from one to ten. The cubic regression model was used for predicting time spent on debugging errors above ten bugs. Results show that the random pair programmers spent an average time of 21.88 min/error while the individual programmers spent a lesser time of 16.57min/error.
Pattern and Feeder Design for the Production of Grey Cast Iron Brackets
(IUP Journal of Mechanical Engineering, 2013-08-01) Mary Adebola Ajiboye; Matthew Sunday Abolarin; Ajiboye, Johnson Adegbenga
In this paper, the design and production of sand casting for a gray cast iron bracket was carried out. The bracket was divided into different sections called Appendages A,B,C and D, and Ribs E and F. Efficient feeder design is important so as to minimize casting defects such as porosity and incomplete filling to the barest minimum. The feeder or riser is used to feed metal to the casting as it solidifies; therefore, they are designed and positioned such as to ensure filling the cavity during solidification. The implication of this is that the riser must be designed to be large enough so that it solidifies only after the casting and it should contain a sufficient volume of metal capable of supplying the shrinkage contraction which occurs on cooling from the casting temperature to the completion of solidification. Based on the feeder design in this work, two bracket castings were produced.
Performance Analysis of Data Normalization Methods
(International Engineering Conference 2017, 2017-10-17) Ajiboye, Johnson Adegbenga; Aibinu M.A
Statistical Data Normalization is a very important input preprocessing operation that should be done before data is fed into the training network. However, there is need for a suitable selection of normalization technique since normalization on the input has potential of varying the structure of the data and may impact on the outcome of the analysis. This paper investigates and evaluates some important statistical normalization techniques by studying thirty published papers that used wine dataset available in the UCI repository and their impact on performance accuracy. Results reveal that Min-Max normalization technique had the best performance accuracy of 95.91% on the average among all the other normalization types.
Performance Analysis of Statistical Time Division Multiplexing Systems
(Leonardo Electronic Journal of Practices and Technologies, 2010) Ajiboye, Johnson Adegbenga; Yinusa Ademola Adediran
Multiplexing is a way of accommodating many input sources of a low capacity over a high capacity outgoing channel. Statistical Time Division Multiplexing (STDM) is a technique that allows the number of users to be multiplexed over the channel more than the channel can afford. The STDM normally exploits unused time slots by the non-active users and allocates those slots for the active users. Therefore STDM is appropriate for bursty sources. In this way STDM normally utilizes channel bandwidth better than traditional Time Division Multiplexing (TDM). In this work, the statistical multiplexer is viewed as M/M/1queuing system and the performance is measured by comparing analytical results to simulation results using Matlab. The index used to determine the performance of the statistical multiplexer is the number of packets both in the system and the queue. Comparison of analytical results was also done between M/M/1 and M/M/2 and also between M/M/1 and M/D/1 queue systems. At high utilizations, M/M/2 performs better than M/M/1. M/D/1 also outperforms M/M1.
Performance Analysis of Statistical Time Division Multiplexing Systems
(Leonardo Electronic Journal of Practices and Technologies, 2010-01) Ajiboye, Johnson Adegbenga; Yinusa Ademola Adediran
Multiplexing is a way of accommodating many input sources of a low capacity over a high capacity outgoing channel. Statistical Time Division Multiplexing (STDM) is a technique that allows the number of users to be multiplexed over the channel more than the channel can afford. The STDM normally exploits unused time slots by the non-active users and allocates those slots for the active users. Therefore STDM is appropriate for bursty sources. In this way STDM normally utilizes channel bandwidth better than traditional Time Division Multiplexing (TDM). In this work, the statistical multiplexer is viewed as M/M/1queuing system and the performance is measured by comparing analytical results to simulation results using Matlab. The index used to determine the performance of the statistical multiplexer is the number of packets both in the system and the queue. Comparison of analytical results was also done between M/M/1 and M/M/2 and also between M/M/1 and M/D/1 queue systems. At high utilizations, M/M/2 performs better than M/M/1. M/D/1 also outperforms M/M1.