Faculty of Technology

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    Open Access
    A comparison of different formulations of offset-free nonlinear model predictive control
    (Department of Chemical Engineering, Obafemi Awolowo University, 2023) AYOADE, Micheal Temitope
    This study developed the simulation model of the different algorithms for offset-free nonlinear model predictive control (NMPC), applied the developed simulation model on selected benchmarked processes and on an experimental process rig. The study then made comparison among the different formulations. These were with a view to comparing the various methods of designing offset-free nonlinear model predictive control.
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    Open Access
    A study of an integrated approach to the adoption of solar photovoltaic water pumping technology in Nigeria
    (Department of Technology management, Falculty of Technology Obafemi Awolowo University, 2005) Anthony Dumebi OKONTA
    This study appraised the technical performance, cost and impact of existing solar photovoltaic water pumping (PVP) systems with the aim of developing a framework for the adoption of the system in Nigeria.
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    Open Access
    A study of Technological capabilities and innovations in the furniture making industry in southwestern Nigeria.
    (Department of Technology Management, Faculty of Technology, Obafemi Awolowo University, 2013) Jide Joseph OBEMBE
    The study assessed the level of technology capabilities in the furniture making industry in Southwestern Nigeria. it also examined the nature and extent of innovations as well as the factors influencing technology learning and innovations in the industry . it evaluated the effect of technology capabilities, innovations and clustering on the performance of the firms in furniture industry.
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    Open Access
    A study of the effect of gravity on the hydrolyzate produced from brewers waste for bioethanol production.
    (Department of Chemical Engineering, Falculty of Sciences, 2021) MUOGHALU, Joseph Chinedu.
    This study characterized the brewers waste for its lignocellulosic contents and other physicochemical properties. It also carried out the enzymatic hydrolysis of the brewers’ waste in addition to investigating the effect of gravity on the kinetics of the hydrolysis. The optimization and production of bioethanol from the hydrolysates using a hybrid of Saccharomyces cerevisiae and Saccharomyces paradoxus. These were with a view to studying the effect of gravity on the hydrolyzate used for the production of bioethanol from brewers’ waste
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    Open Access
    An Appraisal of GSM Telecommunications services delivery in Lagos and Oyo state of Nigeria.
    (Department of Technology Management, Faculty of Technology, Obafemi Awolowo University, 2008) Abdul-hammed, Taofeek Adekune
    The study appraised the quality, volume, and capacity of the telecommunication facilities of the GSM service providers in Lagos and Oyo States of Nigeria. This was to develop strategies for improved service delivery in the industry.
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    Open Access
    An evaluation of the Nigerian innovation system and technological capability building in the manufacturing sector
    (Department of Technology Management, Faculty of Technology , Obafemi Awolowo University., 2005) OKE, Joseph Sunday
    This study evaluated the knowledge generation and utilization performances and the operational environment of the Nigerian innovation system with the aim of establishing the level of technological capability building in the manufacturing sector
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    Open Access
    Capability development in adopting active technology transfer stratrgy in Nigerian industries
    (Department of Technology management, Faculty of Technology, Obafemi Awolowo University., 1998) Ephraim Chukwuma OKEJIRI
    The main technology acquisition strategy of most developing countries including Nigeria is based on the concept of technology transfer which emphasizes importation of production technology. This development strategy which emerged post second world war era had roots in the evolutionary theory of social change.
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    Open Access
    Comparative studies on the effect of dying methods on quality properties of yellow fleshed sweet potato flour
    (Department of Food Science and Technolgy, Faculty of Technology, Obafemi Awolowo Universty, Ile Ife, 2022) BADIORA Aishat Olanike
    This study optimized the processing parameters of yellow-fleshed sweet potato flour (YFSP) using drum drier; compared the quality properties (proximate composition; mineral content, physicochemical, pasting, functional and rehydration properties) of flour produced from sun; oven and drum drier and determined the sensory properties of the reconstituted sweet potato flour. These were with a view to producing acceptable YFSP flour using different drying procedures. The tubers were weighed, sorted, washed, peeled, diced, wet milled into slurry for drum dried samples while oven and sun-dried samples were milled, sifted, weighed and packaged. The pretreatments and drying conditions were blanching at 85 ºC for 3mins 30secs, steam cooking at 120 °C for 2mins, sun drying (3 – 4 days at 27 ± 2 °C), oven drying (70 °C for 8 hours) and drum drying at 150 ºC, 10 rpm, 100 ml (84.05%). The proximate composition, mineral content, physicochemical, pasting, functional, rehydration and sensory evaluation of reconstituted YFSP dough were determined using standard methods. Appropriate descriptive and inferential statistics were used to analyze the data. The proximate composition of the samples showed that oven drying method decreased the moisture content of untreated and treated YFSP flour samples (4.88 – 5.31%) and the ash content (1.50 – 1.62%). All the drying methods increased the carbohydrate contents (73.15 – 81.33%) of YFSP flour samples. Sulphiting decreased the pH of the treated samples (5.58 - 5.90) while untreated sun and drum dried samples had increased pH (6.12 - 6.47). Drum drying method increased the mean particle size of drum dried samples compared to other methods. Untreated and treated samples had lower water absorption capacity (WAC) of 106.5 – 126% and oil absorption capacity (OAC) of 83.5 – 106%. Pretreatment reduced the WAC and OAC of YFSP flour samples. Drum drying method increased the WAC (531%) and OAC (168%) of the drum dried flour samples while it decreased the gelatinization temperature (78.5 ºC) and dispersibility (35%) of the samples. Swelling and rehydration capacities of untreated and treated samples increased as the drying temperatures increased from 80 and 90 ºC. The results showed that drying methods had effect on the pasting profile of the flour samples with the drum dried samples having the lowest values compared to other samples. The mineral contents: calcium (0.47 – 1.37 mg/100 g) and potassium (0.37 – 0.47 mg/100 g) of all the flour samples decreased during pretreatment and processing. Blanched sun-dried samples were the best overall flour based on the sensory properties (colour, taste, texture, mouthfeel and overall acceptability) while drum dried samples had the best functional properties based on water and oil absorption, swelling and rehydration capacity at 28 ± 2 ºC, 60 ºC and 70 ºC. The reconstituted dough from sun and oven drying methods were acceptable by the panelists, except for the drum dried dough. However, dough of steam cooked and sun-dried samples were ranked best. The study concluded that acceptable yellow-fleshed sweet potato flour could be produced from yellow fleshed sweet potato tubers by employing either of sun drying, oven drying or drum drying methods.
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    Open Access
    Developement of a Scenario Based Emergency Response Model for Flooding in Nigeria
    (The Department of Computer Science and Engeneering, Faculty of Technology, Obafemi Awolowo University., 2022) AKHAINE, Victor Emuata
    This Study characterized factors and collected data responsible for flooding, formulated a scenario-based model using the characterized factors and data collected, and simulated and evaluated a model. This was with a view to aiding the planning phase of response agencies by reducing uncertainties through synthetic scenarios. Data based on factors responsible for flooding, were elicited by interviewing experts at the Nigerian Hydrological Service Agency (NHSA), combining systems theory with Delphi method and Cross impact analysis the scenario based model was developed and simulated in python programing language. The causal factors elicited in the course of the interview were categorized into Initial Conditions, Dynamic Events and Outcome Events. In total there were 24 events. The response from the experts were then used to create a probability scale to rank relationships between the events which served as input to the model to generate 6 scenarios, these scenarios were then displayed in graphs. The model was evaluated for accuracy, precision, internal consistency and root mean squared error and verified by comparing the output against recurring events from historical analysis. The results showed that the model had a precision and accuracy of 100% which represents the predictive capability and RMSE of 5.44. the dataset gotten from the experts had an internal consistency of 0.53, 0.7381, and 0.82 based on 3 set of questions in the Delphi questionnaire. Out of the 6 scenarios, flooding had severe impact in scenarios 0, 1,3, and 5 which showed high probability of human casualties, huge economic losses and social unrest. Scenario 4 however showed a reduction of the probability of human casualties and social unrest with the exception of economic losses. In order to further verify the scenarios generated by the model, all the recurring events in the study area were equated to a 100% and then compared with the average accuracy of the scenarios generated by the developed model which was 57.50%. xi The study concluded that the model results formed the basis to develop a dashboard to identify future events that are pivotal in disaster response, and because of this, proactive measures could be taken by the appropriate agencies to respond towards mitigating flooding
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    Open Access
    Development and characterization of banana - fibre reinforced polymar composities.
    (Department of Chemical Engineering, Faculty of Technology, Obafemi Awolowo University., 2022) ILESANMI Olusola Joshua
    This study optimized a production process for banana-fibre composite suitable for engineering application, characterized the banana-fibre composites and established the influence of fibre loading and fibre length on the mechanical properties of the composites. This was with a view to developing a new class of environment-friendly natural-fibre reinforced composites suitable for engineering applications. Banana pseudo stem was collected from a local source from which banana fibres were extracted. Postconsumer PET bottles were obtained from local sources and shredded, washed and oven-dried at 110 oC for 2 hours. The shredded PET bottles were subjected to de-polymerization process via glycolysis in the presence of NaOH as a catalyst. Central composite design was used to generate 26 experimental runs for each mechanical property to be investigated. Fibre length (mm) and fibre content (%) were the two numeric factors considered while alkaline treatment was the categoric factor considered. Hand lay-up technique was used to fabricate the composites, ensuring a horizontal fiber alignment and a unidirectional fiber orientation for all the composites prepared. The polymer composites were left to cure for 24 hours at room temperature after which they were characterized for flexural, tensile and impact strengths. Modelling and optimization of the mechanical properties were carried out using Response surface methodology (RSM). The data obtained for the mechanical properties were fitted as second order equations. Analysis of variance (ANOVA), residual analysis, response surface plots and diagnostic plots were used to evaluate the validity of the models.The results showed that fibre length and fibre content had a significant impact on the flexural strength, tensile strength and impact strength of banana-fibre reinforced polymer composites. Quadratic models were developed for each of the mechanical tests and they were found to provide a good fit with experimental data. There was an increase in the flexural strength of the banana-fibre reinforced polymer composites as the fibre length increased up to 70 mm and as the fibre content increased up to 40%. However, flexural strength decreased as the fibre length further increased up to 80 mm and as the fibre content further increased up to 50%. Polymer composite with 70 mm fibre length and 40% treated fibre content gave the maximum flexural strength of about 3.6 MPa. There was an increase in the tensile and impact strengths of the banana-fibre reinforced polymer composites as the fibre length increased up to 50 mm and as the fibre content increased up to 40%. However, as the fibre length further increased up to 60 mm and as the fibre content further increased up to 50%, the tensile and impact strengths decreased. Polymer composite with 50 mm fibre length and 40% fibre content gave the maximum tensile strength of about 0.765 MPa and maximum impact strength of 9.99 J. The findings of this study showed that development and characterization of banana-fibre reinforced polymer composite could be achieved. Also, varying the fibre length and fibre content of natural-fibre reinforced polymer composites would improve their mechanical properties.
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    Development of a Drug Recommender System
    (The Department of Computer Science and Engineering, Faculty of Technology, Obafeim Awolowo University., 2024) EGBI, Alilu Grace
    This study elicited and analysed data on patients, drugs and disease. The study then designed a drug recommender model, implemented the model and tested the performance of the system. These were with a view to developing a drug recommender system that recommends appropriate drug(s) for the treatment of an ailment. Patients’ data were elicited from Medical Information Mart for Intensive Care – IV (MIMIC-IV), a deidentified clinical data of patient admitted in ICU at Beth Isreal Deaconess Medical Center (BIDMC). Drugs data were elicited from Drugs.com. Disease treatment knowledge were elicited from the guidelines on the treatment of Peptic Ulcer Disease (PUD) provided by the Japanese Association of Gastroenterologists. These data acquired were analysed using various functions in the Pandas library. The model for the recommender system was designed based on the Hybrid recommendation approach by combining clustering algorithm, Collaborative filtering approach (CF) and Knowledge-Based filtering approach (KBF). The factors that were considered for recommending appropriate drugs were age of patient, gender of patient, body weight, allergies and drug interactions. The model designed was implemented using the Python Programming Language version 3.6.3 with Flask framework for web development and Visual Studio Code as the Integrated Development Environment (IDE). And the performance of the system was evaluated using Precision, Recall, and Root Mean Squared Error (RMSE). The evaluation was carried out in two phases; Firstly, the CF component was evaluated by splitting the dataset from MIMIV-IV into 70% (60,018) train set and 30% (25,722) test set. Secondly, the KBF component was evaluated using 30 different cases. The evaluation for this was computed manually by comparing the recommendation results from the system with that of an expert. For the CF aspect of the DRS, the system had a precision score of 85.48%, a recall score of 85.58% and a RMSE score of 0.74. The precision result shows that the system has an 85.48% bability in making relevant recommendations. The recall score shows that the system has an 85.58% ability in recommending relevant drugs from all available relevant drugs. The RMSE score of 0.74 shows that the recommended drugs are far from the actual drugs prescribed. For the KBF aspect of the DRS, the system achieved a Precision of 77%, a recall of 83% and a RMSE of 0.24. The system’s Precision and Recall scores were lower when the KBF was added. This study concluded that the addition of the KBF reduced the error rate between actual recommendations and predicted recommendations. So, the system had a high ability in recommending appropriate drugs for PUD.
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    Open Access
    Development of a microcontroller-based integration of renewable energy sources for implementation of a hybrid power supply system.
    (Department of Electronic and Electrical Enigneering, Faculty of Technology, Obafemi Awolowo University., 2023) SAMSON Joseph Bukola
    This study determined the appropriate size for each of the renewable energy sources (RES) to be integrated, developed a microcontroller-based system capable of coordinating and monitoring the energy output power flow of the sources, and simulated and evaluated the performances of the system. This was done with a view to providing a sustainable solution for electrification of areas not connected to main power grid. The wind speed, solar radiation and load demand data of the study site were obtained from Obafemi Awolowo University, Ile-Ife and then averaged into 1-hour intervals for different geographical seasons. The sequential quadratic programming (SQP) approach was used in the study to determine appropriate and economically viable sizes for the integrated energy systems. The SQP approach was used in the study to find optimal and cost-effective sizes for integrated energy systems that meet the specified requirements. Suitable mathematical models, and size optimization were obtained for the system’s components. Using MATLAB (version 2021a), a microcontroller algorithm for optimal power flow in a hybrid renewable energy source (HRES) was both developed and simulated. For the HRES cost analysis, the overall installation cost and cost per kW of each component were estimated, and three different optimal configurations for the site location were compared for techno-economic analysis. The results show that an off-grid energy system based on RES, with biogas backup, is feasible in the examined location. According to the simulation results, renewable energy (RE) contributes 51.4 % of total load demand in December during the academic period of the weekdays and 96.4 % of total load demand over the weekends of the same period in June. The energy contribution from RES from storage facilities ranged between 20.1 % and 44.0 % of total load demand. Among the three different configurations viz wind/PV/pumped-hydro/battery/biogas, PV/wind/battery, and wind/pumped- hydro/biogas, as examined in this work, wind/PV/pumped-hydro/battery/biogas is discovered to be the most cost-effective configuration with Net Present Cost and Levelised Cost of Energy of $3,085,675 and 0.027 $/kW respectively. The optimal and most cost-effective solution proposed configurations consist of 500 kW of PV system, 400 kW wind turbine. In conclusion, the study showed that implementing an off-grid HRES with sufficient storage, utilizing the pumped-hydro storage system, can provide a sustainable solution for electrification of once not connected to the grid.
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    Open Access
    Development of a microcontroller-based integration of renewable energy sources for the implementation of a hybrid power supply system
    (Department of Electronic and Electrical Engineering, Faculty of Technology, OAU., 2023) Samson, Joseph Bukola
    This study determined the appropriate size for each of the renewable energy sources (RES) to be integrated, developed a microcontroller-based system capable of coordinating and monitoring the energy output power flow of the sources, and simulated and evaluated the performances of the system. This was done with a view to providing a sustainable solution for electrification of areas not connected to main power grid.
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    Open Access
    Development of a Segmentation-Based Deformation-Invariant face Recognition model
    (The Department of Computer Science and Engineering, Faculty of Technology, Obafemi Awolowo University., 2022) ALABI, Akeem Adisa
    Facial deformation has been a prominent issue in today’s trend of face recognition being a key product of human’s most frequently observed phenomenon called expression. The fact is that existing models are yet to fully capture aspects of deformation beyond shape and size of the face thus calling for new approaches to improve on present recognition models. This study formulated, implemented and evaluated a segmentation-based model with the view to recognising faces with deformities. A database of face images with different forms of deformation was created by collecting ten (10) different photographs of twenty (20) persons using digital camera and was analysed by discussing their key components. The collected images were grouped into training set and test data. These images were well cropped and then split accordingly through segmentation technique making each of the image features an individual image. The system model was formulated using modified eigenface algorithm incorporated with a three-phase verification key. This gave rise to the introduction of the Aggregated threshold (AT) as against the Uniform Threshold (UT) as the main parameter for the validation of results of comparison during detection and identification of the test images. The system was implemented using Open Computer Vision (i.e. Open CV) with Python programming language. The system evaluation was carried out to determine the role of the Aggregated Threshold as regards to the performance of the model. The evaluation was also extended to determine the behaviour of the system vis-à-vis the change in the pixel evaluation of the set of images. The results obtained showed that the performance of the proposed model outweighed the existing models as far as recognising the test images was concerned. To be precise, all the forty (40) test images were recognised in this model as opposed to the result in the existing model xvi where only 32 out of 40 images were recognized. This represents an increment of 20% accuracy recorded in comparison with the existing model. The use of the Aggregated Threshold through segmentation paved way for harnessing more information from the set of images during training culminating into the successes recorded in this study. It was also observed that the results obtained were similar with little discrepancies in the execution over the range 100x100 down to 50x50 dimensions. In other words, the number of identified test images remained the same with repeated execution of the code. The study concluded that the segmentation procedure introduced in this model gave rise to an enhanced system in the recognition of faces with deformities thereby giving individuals with this problem an opportunity to be recognized by a robust model.
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    Development of a validated dataset and a framework to mitigate bias in facial image processing
    (Department of Computer Science And Engineering, Faculty of Technology, Obafemi Awolowo University, Ile-Ife., 2025) Amarachi, Modester Udefi.
    This study demonstrated the levels of bias in facial image processing arising from a dataset, built a facial image dataset representing the biased population, and formulated an expression and gender recognition model to validate the dataset. It also described a framework showing the needed representation of certain demographic groups to mitigate bias in facial image processing. The performance of the dataset and model were also evaluated. These were with a view to developing a validated dataset and a framework to mitigate bias in facial image processing. A comprehensive review of 40 publicly accessible facial image datasets was conducted. To visualize the racial distribution of the datasets, t-distributed Stochastic Neighbor Embedding (t-SNE) was employed. Oriented FAST and Rotated BRIEF (ORB) were utilized for feature extraction, followed by K-means clustering to group racial features and Principal Component Analysis (PCA) to assess the geo-diversity and bias levels of the datasets. A 64MPX Camera was used to capture facial images in a controlled environment while questionnaires were used to gather the ground truths. A standard labeling convention was employed in labeling the dataset such that each participant was assigned a unique identifier: a string of ten characters as 0001DMY30C. Expression and Gender recognition models were developed using a Convolutional Neural Network Architecture in conjunction with a transfer learning technique. The UTK (University of Tennessee, Knoxville) dataset was used to train machine learning models to establish a framework to mitigate dataset bias. The model was evaluated based on accuracy, precision, and sensitivity metrics, while fairness metrics, such as demographic parity and equalized odds, were used to assess and quantify biases in the framework. From the result obtained, the PCA and k-means algorithms successfully identified the degree of bias in facial image datasets used in the analysis. The PCA also gave a visual representation of the bias levels in the form of scattered plots and bi-plots, where the facial image datasets were distinguished by their bias levels. A total of 3500 facial expression images were collected and used to develop a gender and expression recognition model. The gender recognition model presented an accuracy, precision, and sensitivity of 94%, 94%, and 94%, respectively, while the expression recognition model showed an accuracy, precision, and sensitivity of 96%, 90%, and 90%. The accuracy evaluation performance matrix for each ethnicity: Black, White, Latino, Asian, Indian, and Others is 98%, 92%, 88%, 89%, 88%, and 84%, respectively. The study concluded that the developed validated dataset and the framework were adequate and could be used to mitigate dataset bias in facial image processing. The framework effectively utilized a class weight formula to combat bias.
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    Open Access
    Development of absorption solar dryer with internet-based control system
    (Department of Agricultural and Environmental Engineering, Faculty of Technology, Obafemi Awolowo University., 2023) Olagunju, Titilope Modupe
    This study investigated the effect of different adsorbent filters on the relative humidity of air and selected the most appropriate filter. This study also developed and evaluated an IoT-based control system for possible use in solar dryers. An existing solar dryer was modified by introducing the selected absorbent filter and the developed IoT control system. The performance of the modified solar dryer was evaluated and optimised by determining the effect of the drying kinetics of ginger slices on the quality of the dried products. These were with a view to enhancing the efficiency and effectiveness of the operation of solar dryers. The optimum specification of moisture adsorbent filter was obtained for four adsorbent materials (activated clay, activated charcoal, calcium sulphate, and silica gel). The data obtained for the effect of pack thickness, suction fan speed, and inlet air temperature on the air desiccation performance of the absorbents was fit in polynomial models and optimised to select the best moisture filter. IoT-based control unit was designed using the Arduino Uno microcontroller, which was interfaced with temperature, humidity, and weight sensors, which were programmed to detect and transmit sensors data to cloud server. The selected absorbent filter as well as the developed control system were then incorporated into the existing mixed-mode solar dryer, and the effect of this modification on the drying kinetics of ginger slices was investigated using response surface methodology. Responses such as total time of active drying and equilibrium moisture content were used as performance indicators of the modified dryer. The optimal conditions for the operation of the dryer, was established and the quality (proximate, phytochemicals and colour) of ginger dried at optimum condition was also determined using standard experimental procedures. The results obtained indicate that silica gel was the most effective adsorbent filter under optimal conditions of 2.03 cm layer thickness, with no requirement for the suction fan. The temperature and relative humidity sensors of the control system were effective, with average accuracies of 98.84% and 96.23%, respectively. However, the weight sensor had an average accuracy of 80.04%. This indicated that the load cell used in the study was sensitive to heat, which adversely affected its accuracy. The performance of the modified solar drying system indicates that the modification significantly aided the drying process of ginger slices, with the best drying conditions being an adsorbent layer thickness of 0.5–1.5 cm and an air velocity of 0.5–2.5 m/s. These conditions resulted in the shortest drying time and a final moisture content of 9.83 to 12.14% wb, which is recommended for safe storage of dried ginger. Nevertheless, the most desirable optimum condition for operating the modified solar dryer was found to be an air velocity of 2.5 m/s and an adsorbent thickness of 1.22 cm, which resulted in a final moisture content of 10.72%. The modification of the dryer significantly influenced the proximate and phytochemical composition of ginger slices. This study concluded that the use of an optimised adsorbent filter and an IoT-based control system can significantly improve the drying process, reduce postharvest losses, and enhance the quality of dried agricultural products.
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    Development of an Adsorption Solar Drying with Internet of Things- Based Control System.
    (Department of Agricultural and Environmental Engineering, Faculty of Technology, Obafemi Awolowo University., 2023) Olagunju, Titilope Modupe
    This study investigated the effect of different adsorbent filters on the relative humidity of air and selected the most appropriate filter. This study also developed and evaluated an IoT-based control system for possible use in solar dryers. An existing solar dryer was modified by introducing the selected adsorbent filter and the developed IoT control system. The performance of the modified solar dryer was evaluated and optimised by determining the effect of the drying kinetics of ginger slices on the quality of the dried products. These were with a view to enhancing the efficiency and effectiveness of the operation of solar dryers. The optimum specification of moisture adsorbent filter was obtained for four adsorbent materials (activated clay, activated charcoal, calcium sulphate, and silica gel). The data obtained for the effect of pack thickness, suction fan speed, and inlet air temperature on the air desiccation performance of the adsorbents was fit in polynomial models and optimised to select the best moisture filter. IoT-based control unit was designed using the Arduino Uno microcontroller, which was interfaced with temperature, humidity, and weight sensors, which were programmed to detect and transmit sensors data to cloud server. The selected absorbent filter as well as the developed control system were then incorporated into the existing mixed-mode solar dryer, and the effect of this modification on the drying kinetics of ginger slices was investigated using response surface methodology. Responses such as total time of active drying and equilibrium moisture content were used as performance indicators of the modified dryer. The optimal conditions for the operation of the dryer, was established and the quality (proximate, phytochemicals and colour) of ginger dried at optimum condition was also determined using standard experimental procedures. The results obtained indicate that silica gel was the most effective adsorbent filter under optimal conditions of 2.03 cm layer thickness, with no requirement for the suction fan. The temperature and relative humidity sensors of the control system were effective, with average accuracies of 98.84% and 96.23%, respectively. However, the weight sensor had an average accuracy of 80.04%. This indicated that the load cell used in the study was sensitive to heat, which adversely affected its accuracy. The performance of the modified solar drying system indicates that the modification significantly aided the drying process of ginger slices, with the best drying conditions being an adsorbent layer thickness of 0.5–1.5 cm and an air velocity of 0.5–2.5 m/s. These conditions resulted in the shortest drying time and a final moisture content of 9.83 to 12.14% wb, which is recommended for safe storage of dried ginger. Nevertheless, the most desirable optimum condition for operating the modified solar dryer was found to be an air velocity of 2.5 m/s and an adsorbent thickness of 1.22 cm, which resulted in a final moisture content of 10.72%. The modification of the dryer significantly influenced the proximate and phytochemical composition of ginger slices. This study concluded that the use of an optimised adsorbent filter and an IoT-based control system can significantly improve the drying process, reduce postharvest losses, and enhance the quality of dried agricultural products.
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    Open Access
    Development of an automatic extraction model for Yoruba text.
    (Department of Computer Science, Faculty of Technology, Obafemi Awolowo University., 2023) Ademusire, Adebisi Joseph
    The research collected Yoruba textual data and annotated them. It formulated a machine learning model for Yoruba text and implemented the model. It also evaluated the implemented model. These were with a view to developing a machine learning model for automatic event extraction for Yoruba text. This research employed a multi-faceted approach to achieve its objectives: data were collected through manual methods, including the conversion of Yoruba folktales from print to digital format via typing and subsequent data cleansing. The preprocessing of data was conducted using the Python programming language. A machine learning model, comprising Bidirectional Long Short-Term Memory (Bi-LSTM) Network and Convolutional Neural Network (CNN) architectures was formulated with fine-tuning of hyper parameters tailored for Yoruba text. The model was implemented using Python, and its evaluation was based on the analysis of over 100 unique Yoruba folktale sentences using standard metrics, including accuracy, F-score, precision, and recall. The results were highly promising, with the Bi-LSTM model for trigger and entity identification achieving an accuracy of 87.00%, precision of 91.72%, recall of 68.54%, and F1 score of 76.67%, while the CNN model for event type classification yielded an accuracy of 47.55%, precision of 52.07%, recall of 49.90%, and F1 score of 48.22%. These findings demonstrate the effectiveness of the developed model, especially the Bi-LSTM component, in capturing event triggers within Yoruba texts. This research not only advances the field of NLP but also contributes to the preservation of Yoruba language and culture, providing a well labelled dataset for event extraction benchmarking in Yoruba language. The study concluded the potential for applying advanced natural language processing (NLP) techniques to linguistically diverse languages and underscores the importance of linguistic diversity in the globalized world. It sets the stage for future research in event extraction from underrepresented languages, paving the way for broader applications in information retrieval, story generation, and cultural preservation.
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    Open Access
    Development of an improved tractor-mounted kenaf (Hibiscus Cannabinus) Harvester
    (Department of Agriculture Engineering, Faculty of Technology ,Obafemi Awolowo University, Ile - Ife , Nigeria., 2022) Thomas Adebayo Ayorinde
    The study designed and fabricated an improved tractor-mounted device for kenaf harvesting; it evaluated the performance of the machine developed. It also developed mathematical models for the torque, power and energy for the machine; and validated the models developed. These were with a view to developing a kenaf harvesting technology which will improve kenaf production efficiency. The tractor mounted kenaf harvesting machine has a rotary drive mechanism, which was adopted from a forage harvester. A review of the physical and mechanical properties of kenaf stem was made to ensure the accuracy of the design calculation for shaft, chain drive and gear design. The cutting blades, spur gears, bevel gears was designed and fabricated based on the design calculations. Performance evaluation of the machine was carried out at the kenaf experimental field set up at the Obafemi Awolowo University Teaching and Research Farm. The evaluation of the machine was carried out from 10 to 16 weeks after planting, at 2 weeks interval. The factors considered in the evaluation include; crop maturity, crop varieties and forward speed of the machine. The machine parameters which are constant machine values peculiar to the machine performance evaluation include width of cut, speed of operation, height of cut. The performance indices were theoretical field capacity, field efficiency, effective field capacity and operational loses. The results obtained was analysed using 3-level factorial response surface methodology (RSM) of design expert software. A mathematical model was developed to detemine the cutting behaviour of the machine when modelled as a fixed uniform cantilever. An equation to predict the cutting torque, power and energy requirement of the machine during operation was obtained and validated. The effective field capacity was observed to decrease with increase in plant maturity and increase with increase in forward speed of the machine. The highest effective field capacity recorded was 2.13 ha/day with Ifeken 100 at crop maturity of 10 weeks after planting, and forward speed was 5 km/hr. The field efficiency of the machine was found to decrease with increase in crop maturity, and forward speed of the machine. The highest field efficiency was 97%, with Ifeken 100, crop maturity of 10 weeks after planting, and at forward speed of machine of 2 km/hr. The duration of operation was also observed to increase with increase in maturity, and decreased slightly with increase in forward speed of machine. The highest duration of operation recorded was close to 9 hours, obtained when the crop maturity was 16 weeks after planting, during the harvesting of Ifeken di 400 and forward speed of 2 km/hr. Operatiional losses was observed to be uniform as the crop maturity increased, highest during the harvesting of Ifeken 100 and increased with increasing forward speed of the machine. The least operational losses recorded was 6.9% recorded when the plant maturity was 16 weeks after planting, during the harvest of Cuba 108 and when the forward speed of machine was 2 km/hr. There was good agreement between the predicted and experimental values of the cutting torque, power and energy requirement of the machine. The study concluded that with the current level of performance obtained for the machine in the research, it has the potential for inclusion in kenaf production operation.
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    Embargo
    Development of digital multimedia resources for african tone languages.
    (Department of Computer science and Engineering, Faculty of Technology. Obafemi Awolowo University., 2024) OLORUNLOMERUE, Adam Biodun.
    The study determined the requirement for a digital resources for African tone languages in the context of multiplatform computing applications. It also specified a digital resources framework, designed the computing standard, interface and tool for the resources specified, implemented the designs and evaluated the implemented digital computing resources system. These were with a view to developing a computing tool with a multimedia application for African tone languages.