FACULTY OF SCIENCE
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Item Assessment of Soil Thermal Properties in a Tropical Environment: Ile Ife and Ibadan(Journal of Faculty of Science, University of Ibadan, Ibadan, Nigeria., 2011) Otunla T.A.; Oladiran E.O.Soil thermal properties are crucial parameters that affect soil heat flux. Time series of soil temperature, soil moisture content, and rainfall and soil heat flux were measured at two tropical locations in West Africa during the transition from dry to wet season, and at the peak of rainy season in July. The data were analyzed to estimate soil thermal diffusivity, thermal inertia and volumetric heat capacity. The thermal properties were clearly related to soil moisture (and thus rainfall) throughout the measurement period. The modeled soil heat flux using the soil thermal properties compared favorably with the measured soil heat flux.Item Assessing the Performance of Global Solar Radiation Empirical Models at a Sahelian Site, Sokoto, Nigeria(The Nigerian Association of Mathematical Physics, 2015) Otunla, T.A.; Kolehaje, O. T.In the region where solar radiation data are scarce, the next alternative method is to use solar radiation models to estimate the data needed for some applications such as simulation of crop performance and the design of solar energy conversion devices. In this paper, the validations of fifteen models for estimating monthly mean daily global solar radiation on the horizontal surfaces were conducted at a location in salielian region where there is great potential for solar energy utilization in electricity generation and irrigation. Evaluations of these models were carried out by using the Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE) and t-test. Three of these statistical performance indicators were combined to generate rank score for each model. Temperature based models made the rank of the best three during the wet season. On the annual scale and in the dry season, temperature variations and humidity were combined with sunshine duration to get the best rank of I to 3.Item Variability and Probabilistic Extremes of Some Climatic Elements over Ibadan(2008) Otunla, T.A.; Oladiran, E. O.; Adeniyi M. O.Data on different climatic elements, like monthly rainfall monthly mean relative humidity, monthly lowest relative humidity; monthly mean temperature, monthly mean maximum and minimum temperatures with their monthly extremes values and monthly mean prevailing wind speeds over Ibadan for the months of January through to December during the period of 1979 through to 2005 have been considered to study their variability and to determine the probabilistic extreme values of these elements. The probabilistic extremes values have been computed for 3 time scales: In 1 year out of 4 years, in 1 year out of 10 years and in 1 year out of 25 years- representing relative more frequent events, moderately extreme events and extreme events, respectively.Item Simple and Reliable methods of Estimating Ground Heat Flux at a Tropical location in Nigeria(2019) Otunla, T.A.; Oladiran, E. O.Ground heat flux (Go) plays an important role in the partitioning of energy budget at earth’s surface. The estimates of G0 are required as part of boundary conditions by all general circulation models. In this work, reliability of four simple and computationally cheap models was tested against a more complex and reliable model as the reference. The simple models selected for investigation are: Simple measurement (SM), Percentage of net radiation (PR), Universal function of net radiation (UR), and Linear function of net radiation (LR) models. Force restore model (FR) was used as the reference model. The data of soil temperature measured at the surface and 0.05 m depth, soil heat flux, measured at 0.05m, and net radiation were obtained from Nigerian Micrometeorological Experiment, Ile Ife. Force restore model was first calibrated with direct measurements for soil heat flux at 0.05 m depth with satisfactory result before it was employed to generate reference G0 estimates. Estimates of SM, PR, UR and LR were compared with FR using simple statistics of coefficient of determination (R2), slope, intercept, root mean square error (RMSE) and mean bias error (MBE). The SM model reproduced the day-time and night-time variations of G0 better than all the models that parameterized G0 as a function of net radiation (R2, slope, intercept, RMSE and MBE values of 0.85, 0.87, 3.43W/m2, 32.69, W/m2, -3.70 W/m2 respectively). This model however requires measurement of both soil heat flux and temperature. The LR model generated the best estimates of Go out of all the models that utilized net radiation measurements (R2, slope, intercept, RMSE and MBE values are 0.60, 0.58,4.55 W/m2, 53.81 W/m2 and 3.60 W/m2 respectively) while UR model is the worst. The LR model, though depend only on one measurement, requires site-specific calibrations and can therefore be deployed for gap filling where SM model cannot be used. "Item Impact of Soil Heat Flux Attenuation on Surface Energy Balance Closure(2012) Otunla, T.A.; Oluwafemi, S.M.In surface energy balance (SEB) measurements, ground heat flux (G) is either reconstructed from soil temperatures using analytical method or from the combination of calorimetric method with soil heat flux measured at 0.05 cm depth or more. Soil heat flux signal attenuation is known to increase with depth. This work intends to investigate the impact of this attenuation, which arises from the placement depths of soil temperature and heat flux plates sensors on SEB closure. Ground heat flux was reconstructed from soil heat flux and temperature measurements at two separate depths of 0.05 and 0.10 cm using calorimetric and analytical methods. The two data sets of G were combined with other SEB components to quantify the impact of placement depth of the soil sensors on SEB closure as a change in residual of SEB measurements (ΔRes). For the calorimetric method, the lowest value of ΔRes in the morning hours was -10W/m2 and the peak value during the daytime was +43W/m2. The values of ΔRes fluctuate between ±20 W/m2 in the morning hours and ±42W/m2 during the daytime for the analytical method but with a greater tendency towards positive ΔRes. Thus, SEB closure decreased with the increasing placement depth of the soil sensors, especially during the daytime. The implication of all these results is an irrecoverable signal loss in the soil heat flux as the placement depth of the sensors increases especially during the daytime.Item Estimates of clear-sky solar irradiances over Nigeria(2019) Otunla, T.A.This study attempts to circumvent the problem of paucity of input data required in climatology mapping of clear-sky solar irradiance in Nigeria by computing beam normal (Ebn) and diffuse (Ed) irradiances using a high performance broadband radiative model in the country climate zones. Air temperature, relative humidity and global datasets of ozone thickness and angstrom turbidity were used as input parameters. The biases in the Ebn estimates with NASA datasets across Nigeria (11e25%) are of similar magnitudes with NASA observations with ground measurements. The estimates show persistent negative biases that increased from tropical savannah to semi-arid climate zones (_8 to _24%). The bias in the Ed estimates is only of similar magnitude with NASA in semi-arid climate zone (10%). The Ed estimates show persistent negative biases that increase from semi-arid to tropical savannah across Nigeria (_7 to _54%). Also, the estimates in each climate zone correspond to the expected climatology of water vapour, aerosol turbidity and absolute optical mass. Lastly, the response of Ebn to water vapour absorption and aerosol extinction signals is mostly active in monsoon zone while the response to the signals by Ed are active in all the zones.Item Estimation of Surface Energy Fluxes Using the Penman Monteith Method in a Tropical Station(2010) Adeniyi1, M.O.|; Otunla, T.A.The Penman Monteith (PM) model was applied in the estimation of sensible and latent heat fluxes on Nigerian Micrometeorological Experiment (Nimex_1) field at Obafemi Awolowo University, Ile-Ife, Nigeria, so as to validate its usage by comparing with direct eddy covariance measured fluxes. The resulting fluxes from the PM model were comparable to the measured eddy covariance ones. The root mean squared error (RMSE) ranging from 17.63 to 22.11Wm-2 and 38.72 to 76.08 Wm-2 was obtained for sensible and latent fluxes, respectively. The coefficient of determination for sensible and latent heat fluxes ranged from 0.83 to 0.90 and 0.78 to 0.90, respectively, with trend lines at the origin. The PM model gave a better estimation of sensible heat flux than the latent heat flux. The PM method was found to be rugged with respect to the choice of values for parameters of the correction advective term Fw which requires the inclusion of the relative humidity of the ground and the air near the surface. The resulting fluxes were not significantly dependent on the choice of the parameters, weather measured or assumed. The coefficient of determination between the two sets of computed fluxes were 1 for both sensible and latent heats. The RMSE ranged between 0.89 and 9.22 with the highest RMSE value on day of year (DOY) with the lowest soil moisture.Item Predictive analysis for journal abstracts using polynomial neural networks algorithm(2017-07) Ojo, A. K.Academic journals are an important outlet for dissemination of academic research. In this study, Neural Networks model was used in the prediction of abstracts from The Institute of Electrical and Electronics Engineers (IEEE) Transactions on Computers. Simulation of results was done using the Polynomial Neural Networks algorithm. This algorithm, which is based on Group Method of Data Handling (GMDH) method, utilizes a class of polynomials such as linear, quadratic and modified quadratic. The prediction was done for a period of twenty-four months using a predictive model of three layers and two coefficients. The performance measures used in this study were mean square errors, mean absolute error and root mean square error.Item Twitter data analysis of ministries, department and agencies in Nigeria(2019-10) Ojo, A. K.; Olanrewaju, A. B.The use of social media tools as a means of communication by various ministries, departments and agencies (MDAs) in Nigeria started very late compared with personal use or in the private or corporate sector. The social media tool of interest is Twitter which is a microblogging application and it is becoming a momentous element of the public sector social media agenda. The study revealed the interest of citizens in the activities of the various MDAs in the country, some MDAs are not known to be too active since their activities are not given the required coverage in the contemporary media or the sector seems not to be receiving adequate attention and patronage. This paper made an empirical and methodological contribution to this new body of knowledge by presenting an overview study of general Twitter accounts maintained by the various MDAs of the Nigerian government. Over 70,000 tweets were used from 64 officially available Twitter accounts. It was discovered that the gradual use of Twitter is really creating a more engaging opportunity for the citizens to have firsthand information about the activities of the government agencies. The study revealed that the trend progressed over the years, that is, there was an upward movement in the use of twitter as a means of government citizen engagement over a 10 years’ period. It was discovered that the use of twitter was very high during the office hours and more activities between Mondays and Fridays. The Nigerian Football Federation led the first five MDAs. Most of the devices used by MDAs to access are laptops or desktops, followed by smart phones. Android devices are more in use than iPhone devices. The remaining devices are not popular in the public services.Item Ako, A.(2019-09) Ojo, A. K.This study presents an approach to extracting data from amazon dataset and performing some preprocessing on it by combining the techniques of Bi-Directional Long Short-Term Memory and 1-Dimensional Convolution Neural Network to classify the opinions into targets. After parsing the dataset and identifying desired information, we did some data gathering and preprocessing tasks. The feature selection technique was developed to extract structural features which refer to the content of the review (Parts of Speech Tagging) along with extraction of behavioral features which refer to the meta-data of the review. Both behavioral and structural features of reviews and their targets were extracted. Based on extracted features, a vector was created for each entity which consists of those features. In evaluation phase, these feature vectors were used as inputs of classifier to identify whether they were fake or non-fake entities. It could be seen that the proposed solution has over 90% of the predictions when compared with other work which had 77%. This increase was as a result of the combination of the bidirectional long short-term memory and the convolutional neural network algorithms.