African Journal of Advances in Science and Technology Research <p><strong>African Journal of Advances in Science and Technology Research (AJASTR) </strong>focuses on the most recent scientific research in physics, chemistry, biology, mathematics, and engineering. The journal's goal is to provide a forum for scientists, researchers, and academics to communicate their results and improve scientific knowledge.</p> <p>Original research articles that make a substantial contribution to the understanding of phenomena in science or the creation of breakthrough technologies are welcome in the journal. The journal also promotes an interdisciplinary and multidisciplinary approach that explores the convergence of several scientific domains. The Journal is currently published quarterly in March, June, September, and December of each year.</p> Afropolitan Publications Int'l en-US African Journal of Advances in Science and Technology Research Hybrid Deep Learning Architectural Framework for Analysis of Hateful Sentiment on Twitter (X) <p><em>In recent years, the pervasive use of social media platforms, such as Twitter, has led to an exponential increase in the dissemination of information and opinions. However, this phenomenon has also given rise to the alarming prevalence of hateful sentiment, posing significant challenges for online communities and societal harmony. To address this issue, a Hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) Deep Learning Architectural Framework was designed specifically for the analysis of hateful sentiment in Twitter content. The framework combines the spatial feature extraction capabilities of CNNs with the sequential learning proficiency of LSTMs, aiming to capture both local patterns and long-term dependencies within the textual data. The framework achieves a comprehensive understanding of the sequential and contextual nature of language, thereby enhancing the accuracy of hateful sentiment analysis. To evaluate the effectiveness of the proposed framework, extensive experiments were conducted on two large datasets of labeled tweets containing hateful sentiments. The work was done in two tasks using different datasets and the results demonstrate superior performance in both tasks compared to existing state-of-the-art models. Task 1 generated a 0.82 macro F1-score and 0.92 weighted F1-score, and Task 2 generated a 0.82 macro F1-score and 0.90 weighted F1-score, showcasing the ability of the proposed architecture to discern subtle variations in hate speech, sarcasm, and disguised forms of harmful language. Beyond sentiment analysis, the implications of this research extend to the development of robust tools for fostering a safer online environment.</em></p> Hyellamada Simon Copyright (c) 2024 Hyellamada Simon (Author) 2023-12-31 2023-12-31 13 1 1 20 Binaural Beat Effect on Brainwaves, Stress Management and Its Applications <p><em>The brain is made up of billions of brain cells called neurons, which communicate with each other via electric impulses. Neurochemical processes in human brain are measured by wave function which is nothing but Brain Waves. These waves can be detected by a sensitive machine called electroencephalograph (EEG) machine, which are indirect means of assessing the mind consciousness. These are categorized into four frequency band depending upon consciousness levels. The frequency band include; beta, alpha, theta, and delta waves, which depends on activeness of mind. These waves are the outcome of binaural beat phenomenon which is the auditory brainstem where responses originates in the superior Olivary nucleus of each hemisphere. This technique can also be applied to brainwave entrainment, where binaural beat can be changed through audio binaural beat resonant entrainment techniques by applying sonic frequency through stereo headphone. The experiment to verify the effect of binaural beats on brainwaves was carried out with the following apparatus: An Electroencephalogram Machine (Phoenix Digital EEG Machine), Binaural Beat Audio (10Hz), Stereo headphones. Binaural beat was used to entrain the brainwaves of 10 human subjects for 30 minutes using the electroencephalogram (Phoenix Digital EEG) machine to monitor the changes in brainwaves. The entrained brainwaves were recorded at every 10 minute interval for each subject under study. The data provides evidence that all subjects experienced some level of relaxation as evidenced in the significant change in their brainwaves from low beta (13 Hz) to high theta (7 Hz) and even as low as 6 Hz in one subject. Base on this work, one can deduced, binaural beats could be used to entrain brainwaves, and could be applied to stress management by inducing relaxation through reduction in the brainwaves.</em></p> Hamza Abubakar Hamza Auwal Rabiu Hassan Usman Mohammed Musa Ishaya Sharpson Copyright (c) 2024 Hamza Abubakar Hamza, Auwal Rabiu Hassan, Usman Mohammed, Musa Ishaya Sharpson (Author) 2023-12-31 2023-12-31 13 1 21 29 Understanding the Rudiments of Nigeria’s National Health Policies of 1988, 2004, and 2016 <p><em>Increasing health challenges within the Nigerian health system threaten the sustainability of national health policy development and implementation. The Nigerian government has within 28 years developed three health policy documents, beginning in 1988, revised in 2004, and 2016. Despite these efforts, the implementation challenges linger. In this regard, the study aims to understand the health policy development and implementation prowess from the stakeholder’s perspectives. The methodology adopts a descriptive qualitative study approach. The study was conducted in 12 states of&nbsp;the country, targeting experienced respondents. An in-depth interview with 15 purposively selected respondents from the government, development partners, CSOs, and academia was conducted. The study revealed the contribution of pressure groups to the government of the three National health policies of 1988, 2004, and 2016 respectively, and improvement in health policy implementation in the country. However. the study identifies a lack of synergy between government and private sectors in terms of Private Public Partnerships for policy development and implementation. Therefore, the study suggests the inclusion of a monitoring and evaluation framework in policy implementation processes. Also, a further study that critically assesses the impediment factors to the successful involvement of the private sector in health policy formation should be explored.</em></p> Umar Ibrahim Kabiru Sabitu Sabaatu Elizebeth Danladi Nahuta Copyright (c) 2024 Umar Ibrahim, Kabiru Sabitu, Sabaatu Elizebeth Danladi Nahuta (Author) 2023-12-31 2023-12-31 13 1 30 37 Application of Response Surface Method in Predicting and Optimizing the Engineering Properties of Activated Metakaolin Treated Non-Lateritic Soil <p><em>This study focuses on using response surface methodology (RSM) to predict and optimize the unconfined compressive strength (UCS) and California bearing ratio (CBR) of activated metakaolin (MK) treated non-lateritic soil for road construction purposes. The experimental results of various blends compacted using British standard light, West African standard, and British standard heavy methods were used to create a useful model for overall response variation. The design consists of two design factors, MK and sodium hydroxide (SH), with MK and SH as independent variables, and UCS and CBR as the responses. Predictive equations for the responses were obtained using the independent variables. Statistical analysis and analysis of variance for all responses showed that quadratic models were successful in predicting the UCS and CBR of activated MK-treated non-lateritic soil with R<sup>2</sup> (0.9835-0.9999), Adj R<sup>2</sup> (0.9718-0.9999), and Pred R<sup>2</sup> (0.8776-0.9998). F-values are greater than the critical F-value (3.59), indicating that the factors have a significant effect on the model behaviour. The P value of the models was less than P<sub>α</sub>(0.05), indicating that the factors are significant in predicting the responses. Furthermore, optimized factors were predicted to obtain optimal values for UCS and CBR that met the Nigerian General Specification for road base course usage. These predictions were validated, and a good correlation was observed between the experimental and predicted values, as judged by the absolute relative percent error (0.0232–1.1628). The proposed models are capable of predicting the UCS and CBR values, which can help make early decisions during the construction process.</em></p> Ikara Abdulkarim Ibrahim Yusuf Umar Saeed Muhammed Abbagana Arafat Yero Suleiman Copyright (c) 2024 2024-01-10 2024-01-10 13 1 38 57