Communities in DSpace

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The critical role of hyperparameter tuning in machine learning: Implications for reproducibility and model comparison
(Kwara State University, 2025-12-31) Rafiu Mope Isiaka; Shakirat Ronke Yusuff; Akinbowale Nathaniel Babatunde; Shuaib Babatunde Mohammed
Despite being a fundamental aspect of machine learning model development, hyperparameter tuning remains underreported in the literature. This article highlights the importance of hyperparameter optimisation, outlines common hyperparameters across various algorithms, and discusses the consequences of inadequate hyperparameter documentation. We argue that the lack of transparency in hyperparameter settings impedes reproducibility, hinders fair model comparisons, and contributes to the hyperparameter deception. The importance of hyperparameter tuning in machine learning was demonstrated by comparing the performance of the decision tree, support vector machine and random forest models on Iris, Digits and Breast Cancer datasets using default and tuned hyperparameters. This further justifies the need to document and report the process and values of the hyperparameter settings used in the models. To facilitate this, an architecture that encourages the documentation of the hyperparameters has been proposed. By emphasising the need for comprehensive reporting, this study aims to raise awareness and encourage best practices in machine learning research
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Implementation of Yorùbá Unicode generation for an indigenous keyboard
(Kwara State University, 2020) Jumoke Falilat Ajao; Ronke Seyi Babatunde; Shakirat Ronke Yusuff; Suliyat Oyindamola Asapetu
Characters are generally represented on standard keyboards by the use of coding schemes such as ASCII and Unicode but some characters of the Yorùbá language were not captured because of the accent and diacritic signs inherent in Yorùbá language. Coding representation for Yorùbá characters has become a key problem in circuit implementations of keyboards for typing Yorùbá documents correctly. The standard keyboard layouts do not have a simple key combination for all the characters. To represent Yorùbá characters in human-computer interaction, this paper proposes the use of Unicode for the deployment of Yorùbá keyboard for effective and efficient typing of documents in Yorùbá language. The approach used for the development of the Yorùbá keyboard uses both binary and hexadecimal representation of the coding standards to codify Yorùbá characters with their diacritic signs and the under dot. This dimension introduces the complex Yorùbá character coding representations using a single code point standard. The generated Unicode point was transformed into HTML entities. The HTML entities generated were converted to its character equivalent for the Yorùbá keyboard. The new Unicode was compared with the results of the two encoding standard scheme using the bit relationships of upper and lower case characters to ascertain conformity of the new Unicode with the standard encoding scheme. This provided some insights about the efficient representation of Yorùbá character scheme. The representation is expected to quickly identify solutions to the design of Yorùbá keyboards and signage.
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Development of a Language Translator Model for Yoruba Language using Bidirectional Long Short-Term Memory Encoder
(Faculty of Information and Communication Technology, Kwara State University, Malete., 2024) Jumoke Falilat AJAO; Abdulazeez Olorundare Ajao; Rafiu Mope ISIAKA; Shakirat Ronke YUSUFF; Abdullahi YAHAYA
Nigeria is a nation of vast ethnic diversity, encompassing a multitude of cultures, languages, and values. These differences often present significant communication barriers among its various ethnic groups. To bring the language barrier, Google has integrated several Nigerian languages into its translation model. This study focuses on the development of an automatic speech recognition (ASR) system for Yoruba, one of Nigeria’s indigenous languages. Speech dataset was collected from native Yoruba speakers and subjected to extensive preprocessing eliminate background noise introduced during the recording process. The preprocessed data was then transformed into a speech spectrogram, serving as input to a bidirectional long short-term memory (BiLSTM) model. The hyperparameters of the BiLSTM model were optimised for improved performance. The translation model was evaluated using metrics such as BLEU, METEOR, and ROUGUE. Results demonstrated significant improvements in the ASR model’s ability to accurately transcribe and translate Yoruba language speech. This advancement translation accuracy highlights the potential for better cross-linguistic communication among Nigeria’s ethnic groups, fostering greater inclusivity and understanding. This study contributes to ongoing efforts to incorporate underrepresented languages in global translation models, addressing the challenge of language diversity in multilingual societies.
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Gender recognition using local binary pattern and Naive Bayes classifier
(Journal of computer Science and its Application, 2016) Babatunde, R. S.; Abdulsalam, S. O.; Yusuff, S. R.; Babatunde, A. N.
Human face provides important visual information for gender perception. Ability to recognize a particular gender is very important for the purpose of differentiation. Automatic gender classification has many important applications, for example, intelligent user interface, surveillance, identity authentication, access control and human-computer interaction amongst others. Gender recognition is a fundamental task for human beings, as many social functions critically depend on the correct gender perception. Consequently, real-world applications require gender classification on real-life faces, which is much more challenging due to significant appearance variations in unconstrained scenarios. In this study, Local Binary Pattern is used to detect the occurrence of a face in a given image by reading the texture change within the regions of the image, while Naive Bayes Classifier was used for the gender classification. From the results obtained, the gender correlation was 100% and the highest accuracy of the result obtained was 99%. The system can be employed for use in scenarios where real time gender recognition is required.
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Examining students’ perception of surveillance technology and its impact on privacy in educational institutions
(Emerald Publishing Limited, 2026-04-13) Durodolu O. O.; Shuaibu A. J.; Babatunde V. O.; Yusuff, S. R.
Purpose – The ubiquity of digital surveillance technologies is at the forefront of debates on balancing collective security while ensuring individual privacy. Ethical concerns of individual privacy, freedom and misuse are at the crux of ongoing global discourse, with the integration of artificial intelligence into surveillance further increasing the intrusive nature of these technologies. This study examined students’ perception of surveillance technology and its impact on privacy. Questions articulated from the problematic bordered around the level of awareness, perception on the impact of surveillance technology, attitude towards surveillance and beliefs in the regulation of surveillance in educational institutions among others. Design/methodology/approach – This study was premised on the pragmatic paradigm involving the integration of both quantitative and qualitative approaches. Data were collected from 450 respondents using a structured questionnaire. Findings – Findings revealed a significant association between students’ awareness of surveillance technologies and their frequency of observing them on campus (χ² = 47.80, df = 6, p < 0.001; mixed perceptions of privacy with most respondents (54.9%) feeling their privacy was moderately respected, a notable minority expressing concern over inadequate protection, and nearly a quarter (24.2%) reporting behavioural changes due to being watched; and a statistically significant positive relationship between trust in institutional data handling and confidence in data protection (ρ = 0.144, p < 0.01).The qualitative responses revealed that students acknowledged the usefulness of surveillance for safety, but insisted on clear boundaries regarding scope, usage and access. This study concluded that surveillance in education was a double-edged phenomenon that enhances safety and order but raised several challenges that called for deliberate governance strategies. It was recommended that educational institutions developed clear communication strategies on the use of surveillance technologies and accompany such with privacy protection policies. Originality/value – The findings contribute to academic debates on digital ethics, governance and the balance between security and privacy in learning environments, while offering actionable recommendations for institutions to design communication strategies and privacy policies that safeguard both safety and individual rights.