Elizabeth Toyin Okeniyi

Implementation of Kolmogorov–Smirnov P-value computation in Visual Basic®: implication for Microsoft Excel® library function

This paper investigates methodologies for evaluating the probabilistic value (P-value) of the Kolmogorov–Smirnov (K–S) goodness-of-fit test using algorithmic program development implemented in Microsoft® Visual Basic® (VB). Six methods were examined for the one-sided one-sample and two methods for the two-sided one-sample cumulative sampling distributions in the investigative software implementation that was based on machine-precision arithmetic. For sample sizes n≤2000 considered, results from the Smirnov iterative method found optimal accuracy for K–S P-values≥0.02, while those from the SmirnovD were more accurate for lower P-values for the one-sided one-sample distribution statistics. Also, the Durbin matrix method sustained better P-value results than the Durbin recursion method for the two-sided one-sample tests up to n≤700 sample sizes. Based on these results, an algorithm for Microsoft Excel® function was proposed from which a model function was developed and its implementation was used to test the performance of engineering students in a general engineering course across seven departments.

Wind characteristics and energy potential assessment in Akure, South West Nigeria: econometrics and policy implications

This paper analysed 11 years of daily mean wind-speed data, measured at Akure, Ondo State, Nigeria, using Weibull and Rayleigh distribution functions. While both distributions showed good agreements in extreme-value estimation patterns, investigation of their wind-speed characteristics modelling criteria, using goodness-of-fit statistics, revealed that the wind data followed the Weibull more than Rayleigh. Monthly wind-speed of Akure city ranged from 1.41 to 4.24 m/s by the Weibull fittings and from 1.40 to 4.16 m/s by the Rayleigh fittings. Overall results, of 2.71 m/s (Weibull) or 2.70 m/s (Rayleigh) mean wind-speed and 18.51 W/m2 (Weibull) or 22.26 W/m2 (Rayleigh) mean power density, indicated Akure a low wind-speed site, requiring low wind-speed turbine for generating wind energy. Econometric analyses of power output simulations using such turbine system resulted in affordable wind energy cost. These bear policy implications for sustainable wind energy usage in this and similar regions of the world.

Assessments of Wind-Energy Potential in Selected Sites from Three Geopolitical Zones in Nigeria: Implications for Renewable/Sustainable Rural Electrification

Electricity generation in rural communities is an acute problem militating against socioeconomic well-being of the populace in these communities in developing countries, including Nigeria. In this paper, assessments of wind-energy potential in selected sites from three major geopolitical zones of Nigeria were investigated. For this, daily wind-speed data from Katsina in northern, Warri in southwestern and Calabar in southeastern Nigeria were analysed using the Gumbel and the Weibull probability distributions for assessing wind-energy potential as a renewable/sustainable solution for the countrys rural-electrification problems. Results showed that the wind-speed models identified Katsina with higher wind-speed class than both Warri and Calabar that were otherwise identified as low wind-speed sites. However, econometrics of electricity power simulation at different hub heights of low wind-speed turbine systems showed that the cost of electric-power generation in the three study sites was converging to affordable cost per kWh of electric energy from the wind resource at each site. These power simulations identified cost/kWh of electricity generation at Kaduna as €0.0507, at Warri as €0.0774, and at Calabar as €0.0819. These bare positive implications on renewable/sustainable rural electrification in the study sites even as requisite options for promoting utilization of this viable wind-resource energy in the remote communities in the environs of the study sites were suggested.

Biochemical Characterisation of the Leaf of Morinda Lucida : Prospects for Environmentally-Friendly Steel-Rebar Corrosion-Protection in Aggressive Medium

This paper employs atomic absorption spectroscopy (AAS), Fourier transform infrared spectroscopy (FTIR) and phytochemical screening methods for biochemical characterisation of the inorganic and organic constituents of the leaf of Morinda lucida. AAS results showed that this well-known medicinal-plant is high in iron (Fe = 5143.54 µg/g), low in cadmium (Cd = 2.9506 µg/g) and does not contain chromium (Cr). Also, Euclidean hit-list from the FT-IR instrument suggests Morinda lucida leaf-extract contains S-, N-, Br- and O- containing heteroatoms. The phytochemical analyses indicated presence of tannins, phlobatannins, saponins, flavonoids and terpenoids. These results bare prospects on suitability of leaf-extract from Morinda lucida for environmentally-friendly steel-rebar corrosion-protection in aggressive medium. Preliminary tests based on this showed that use of 0.083 wt% cement of Morinda lucida retarded steel-rebar total-corrosion and eventually reduced corrosion rate as admixture in duplicated 3.5% NaCl-immersed concretes, relative to control samples in the same medium.

Programming Development of Kolmogorov-Smirnov Goodness-of-Fit Testing of Data Normality as a Microsoft Excel® Library Function

This paper deliberates on the programming development of the Kolmogorov-Smirnov goodness-of-fit testing of data Normality as a library function in the Microsoft Excel® spreadsheet software, in which researchers normally store data for analysis and processing. The algorithmic program procedure utilised developed implementation of the Normality Kolmogorov-Smirnov D statistics for the one-sided and the two-sided test criteria as a library function in the Microsoft Excel® environment. For these programming developments, the Visual Basic for Applications® was employed for deploying macro embedment in the spreadsheet software. Successful programming development of the Normality K-S D statistics fosters implementation of the Normality K-S p-value estimation procedure also as a library function in the Microsoft Excel® environment. Test-applications of these programming developments in the study portray potency of accurate, speedy and economical procedure for testing compatibility of univariate data of real numbers to the Normal distribution, for datasets of n ≤ 2000 sample size.

Smart campus: Data on energy generation costs from distributed generation systems of electrical energy in a Nigerian University

This data article presents comparisons of energy generation costs from gas-fired turbine and diesel-powered systems of distributed generation type of electrical energy in Covenant University, Ota, Nigeria, a smart university campus driven by Information and Communication Technologies (ICT). Cumulative monthly data of the energy generation costs, for consumption in the institution, from the two modes electric power, which was produced at locations closed to the community consuming the energy, were recorded for the period spanning January to December 2017. By these, energy generation costs from the turbine system proceed from the gas-firing whereas the generation cost data from the diesel-powered generator also include data on maintenance cost for this mode of electrical power generation. These energy generation cost data that were presented in tables and graphs employ descriptive probability distribution and goodness-of-fit tests of statistical significance as the methods for the data detailing and comparisons. Information details from this data of energy generation costs are useful for furthering research developments and aiding energy stakeholders and decision-makers in the formulation of policies on energy generation modes, economic valuation in terms of costing and management for attaining energy-efficient/smart educational environment.

Effects of Dialium guineense Based Zinc Nanoparticle Material on the Inhibition of Microbes Inducing Microbiologically Influenced Corrosion

This paper investigates the effects of Dialium guineense based zinc nanoparticle material on the inhibition of microbes inducing microbiologically influenced corrosion (MIC) in metals. Extract of leaf from the natural plant were used as precursor for zinc nanoparticle material, which was characterized by scanning electron microscopy and energy dispersive spectroscopy (SEM + EDS) instrument. Sensitivity of the developed zinc bio-nanoparticle material from this on different strains of microbes that are known to induce microbiologically influenced corrosion, in metallic materials, was then studied and compared with that obtained from a commercial antibiotic employed as control. Results showed that the biomaterial capped nanoparticle exhibited inhibited growth of the studied different MIC inducing microbes. Zones of inhibition, the sensitivity measure of the biosynthesized material against the microbial strains either surpassed or compared well with the zones of inhibition from the commercial antibiotic (control). These results engender implication on the prospects of the zinc bio-nanoparticle usages in corrosion inhibition and protection system for metals in microbial corrosion influencing environment.

Investigating Solanum Aethiopicum Leaf-Extract and Sodium-Dichromate Effects on Steel-Rebar Corrosion in Saline/Marine Simulating-Environment: Implications on Sustainable Alternative for Environmentally-Hazardous Inhibitor

This paper investigates Solanum aethiopicum leaf-extract and the well-known but environmentally-hazardous sodium-dichromate inhibitor effects on concrete steel-rebar corrosion in 3.5% NaCl medium (simulating saline/marine environment). Different equal-concentration models (wt% cement) of the natural-plant leaf-extract and of sodium-dichromate were admixed in steel-reinforced concrete slabs from which electrochemical test-measurements were obtained for comparing admixture performance. Test-results, analyzed as per ASTM G16-95 R04, showed that only the 0.083% sodium-dichromate admixture outperformed the 0.083% Solanum aethiopicum leaf-extract in corrosion-inhibition effectiveness. The other natural-plant leaf-extract exhibited better inhibition-efficiency performance than their equal-concentration models of sodium-dichromate. The 0.25% Solanum aethiopicum leaf-extract exhibited optimal performance, η = 98.28%, at inhibiting steel-rebar corrosion among the also effective different concentrations of the plant-extract and of sodium-dichromate admixtures employed. These and phytochemical test-results bare indications that Solanum aethiopicum leaf-extract is a suitable, sustainable and eco-friendly alternative for the environmentally-hazardous sodium-dichromate inhibitor of steel-rebar corrosion in concrete designed for saline/marine environments.

Bioremediation: Data on Pseudomonas aeruginosa Effects on the Bioremediation of Crude Oil Polluted Soil

This data article details Pseudomonas aeruginosa effects on the bioremediation of soil that had been polluted by different concentrations, 5% w/w and 8% w/w, of raw (for simulating oil spills from well-heads) and treated (for simulating oil spills from flow lines/storage tanks) crude oil. UV/VIS spectrophotometry instrumentation was used for obtaining absorbance measurements from the Nigerian Escravos Light blend (sourced from Chevron® Nigeria) of crude oil polluting soil samples, which, thus, also simulates light and heavy onshore oil spillage scenarios, in a 30-day measurement design. Data on bioremediation effects of Pseudomonas aeruginosa added to the crude oil polluted soil samples, and which were monitored at intervals via the absorbance measurement techniques, are presented in tables with ensuing analyses for describing and validating the data presented in graphs. Information from the presented data in this article is useful to researchers, the oil industries, oil prospecting communities, governments and stakeholders involved in finding solution approach to the challenges of onshore oil spills. This information can also be used for furthering research on bioremediation kinetics such as biostimulant analyses, polluting hydrocarbon content/degradation detailing, by Pseudomonas aeruginosa strain of microorganism, on petroleum pollutant removal from soil that had been polluted by crude oil spillage.

C3H7NO2S effect on concrete steel-rebar corrosion in 0.5 M H2SO4 simulating industrial/microbial environment

This paper investigates C3H7NO2S (Cysteine) effect on the inhibition of reinforcing steel corrosion in concrete immersed in 0.5 M H2SO4, for simulating industrial/microbial environment. Different C3H7NO2S concentrations were admixed, in duplicates, in steel-reinforced concrete samples that were partially immersed in the acidic sulphate environment. Electrochemical monitoring techniques of open circuit potential, as per ASTM C876-91 R99, and corrosion rate, by linear polarization resistance, were then employed for studying anticorrosion effect in steel-reinforced concrete samples by the organic hydrocarbon admixture. Analyses of electrochemical test-data followed ASTM G16-95 R04 prescriptions including probability distribution modeling with significant testing by Kolmogorov-Smirnov and students t-tests statistics. Results established that all datasets of corrosion potential distributed like the Normal, the Gumbel and the Weibull distributions but that only the Weibull model described all the corrosion rate datasets in the study, as per the Kolmogorov-Smirnov test-statistics. Results of the students t-test showed that differences of corrosion test-data between duplicated samples with the same C3H7NO2S concentrations were not statistically significant. These results indicated that 0.06878 M C3H7NO2S exhibited optimal inhibition efficiency η = 90.52±1.29% on reinforcing steel corrosion in the concrete samples immersed in 0.5 M H2SO4, simulating industrial/microbial service-environment.