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- ItemEconomic Selection of Efficient Level of NPK 16:16:16 Fertilizer for Improved Yield Performance of a Maize Variety in the South Guinea Savannah Zone of Nigeria(Journal of Mathematical Theory and Modeling, 2013) Olorede K. O.; Mohammed I. W.; Adeleke B. L.This study investigates effects of different levels of NPK 16:16:16 fertilizer on yield and performance of maize. Data sets were obtained from a study conducted at the University of Ilorin Teaching and Research Farm, faculty of Agriculture, University of Ilorin during the 2010 cropping season. The study was conducted on a maize variety (Swan-1-SR-Y) sourced from Federal Ministry of Agriculture and Water Resources, Abuja, Nigeria using a completely Randomized Design (RCBD) replicated three times. Application of the fertilizer type was done at two equal splits of 2 weeks after planting and immediately after tasseling using ring method of application. The appropriate analysis of variance (ANOVA) model was used to collect observations at 2 weeks interval from week 5 to week 15 after planting on growth variables such as plant height (kg), leaf area (cm2), number of leaves, cob weight (kg) and grain weight (kg) respectively at equally spaced levels 0kg/ha, 30kg/ha, 60kg/ha, 90kg/ha and 120kg/ha of the fertilizer type. Before conducting ANOVA, the data sets were inspected for homogeneity of error variances using Fligner-Killeen test in the R statistical package. Shapiro-Wilk test of normality was used to check normality of the residuals. The normal probability plot showed no indication of outliers and the largest standardized residual was within . NPK 16:16:16 fertilizer level 60 Kg/ha was found to be the most efficient and economical for improving growth and yield performance of the maize variety in the ecological zone. The optimum yield of the maize variety due to application of the NPK 16:16:16 fertilizer levels is in the 13th week after planting.
- ItemPartial Least Squares-Based Classification and Selection of Predictive Variables of Crimes against Properties in Nigeria(Professional Statisticians Society of Nigeria (PSSN), 2017) Olorede K. O.; Yahya W. B.; Garuba A. O.; Banjoko A. W.; Dauda K. A.In this study, the state-of-the-art Partial Least Squares (PLS) based models (PLS-Discriminant analysis (PLS-DA), Sparse PLS-DA (SPLS-DA) and Sparse Generalized PLS (SGPLS)) were employed to model and classify the rate of crimes (low or high) committed against properties across the 36 states in Nigeria and the Federal Capital Territory (FCT). The core variables that are predictive of this crime type in Nigeria were identified using the LASSO penalty method via the PLS. Data on occurrences of cases of offences against property obtained from the data base of Nigerian Police Force were utilized in this study. The missing values due to non-occurrence or non-reportage of crime cases were imputed, using the techniques of multivariate imputation by chained equation. The complete data set were partitioned into training and test sets using 80:20 holdout scheme. The 80% training set was used to build the PLS-based models that were in turn used to predict the overall crime rates of Nigerian cities in the 20% held out test data over 200 Monte-Carlo cross-validation runs. All the PLS-based models yielded good classification of unseen test samples into either of two qualitative classes of high and low crime rates with average Correct Classification Rate (CCR) of 94%. Other performance metrics including sensitivity, specificity, positive and negative predictive values, balance accuracy and diagnostic odds ratio were estimated to further examine their classification efficiencies. The SGPLS identified fewer (just 3 out of 12) core relevant crime variables that are predictive of the overall crime rates in Nigerian states with highest CCR than the SPLS which selected 9 such variables to achieved about the same feat.
- ItemHankel determinants with Fekete-Szegö parameter for a subset of Bazileviˇ c functions linked with Ma-Minda function(PSR Press, 2025-03-29) Lasode, A. O.; Ayinla, R. O.; Bello, R. A.; Amao, A. A.; Fatusin, L. M.; Sambo, Bitrus; Awoyale, O.Consider a unit disk Ω = {z : |z| < 1}. A large subset of the set of analytic-univalent functions defined in Ω is examined in this exploration. This new set contains various subsets of the Yamaguchi and starlike functions, both of which have profound properties in the well-known set of Bazileviˇ c functions. The Ma-Minda function and a few mathematical concepts, including subordination, set theory, infinite series formation and product combination of certain geometric expressions, are used in the definition of the new set. The estimates for the coefficient bounds, the Fekete-Szegö functional with real and complex parameters, and the Hankel determinants with a real parameter are some of the accomplishments. In general, when some parameters are changed within their interval of declarations, the set reduces to a number of recognized sets.
- ItemGenetic Diagnosis, Classification, and Risk Prediction in Cancer Using Next-Generation Sequencing in Oncology(CRC Press, Taylor & Francis Grou, 2024) Dauda, K. A.; Olorede, K. O.; Banjoko, A. W.; Yahya, W. B.; Ayipo, Y. O.In recent years, researchers have been overwhelmed with large-scale genomic data due to an advancement toward data-driven science called next-generation sequencing. Hence, it has been established that if the sequence of a gene is mutated, there is the possibility of unscheduled production of the protein, leading to cancer. The prediction of genes and variants into true and false pathogenic groups, extraction of the most influential genes, and identification of a pattern from this genomic data are of interest to biologists and medical professionals. However, the identification and extraction of these biomarkers and molecular signatures of different cancers among thousands of genes seem complex and problematic. Therefore, this chapter is aimed to develop an algorithm that can aid and provide efficient solutions for gene extraction, identification, and prediction in the realm of next-generation sequencing data. The proposed algorithm consists of three folds: the filtering fold using minimum redundancy maximum relevance (MRMR), the wrapper fold using the Boruta algorithm, and the last fold consisting of the use of deep learning (DL). A comparison assessment was performed on the proposed algorithm and the existing methods using five RNA-seq datasets from a cancer patient. The results revealed that the proposed algorithm significantly outperforms the existing methods in selecting fewer highly relevant genes for the cancer type while maintaining a high classification prediction accuracy.
- ItemHydration Status in Nigeria: A Cross-Sectional Study(Pakistan Journal of Nutrition, 2014) Yunusa Olufadi; Alfred B. O. Soboyejo; Kabir Opeyemi Olorede; Kazeem Adesina DaudaMost literatures on daily water intake are focused on developed countries and to our knowledge; there is limited information on the hydration status of Nigerians. Our objective was to describe daily water intake (DWI) among Nigerian students, develop a model for the prediction of students’ DWI and examine the association between DWI and four predictor variables. Data on DWI for 150 students aged 18-26 years were collected through a survey conducted at Kwara State University in February, 2013 together with information on their age, weight, gender and awareness of dieticians’ recommendation. Our results indicates that students’ DWI varies by gender with male students drinking more than their female counterparts; although, the awareness rate is higher in females than males. We found that nearly half of participants (44%) drank less than 2.7 L of water/day, 25% between 2.7 and 3.7 L/day and 31% reported drinking more than 3.7 L of water/day. Results also revealed that students’ DWI decline with age but increases with weight and one-in-two of the students are unaware of the dangers of poor hydration. Arguably, this study is the first description of DWI among Nigerian students and fills the gap in the literature by developing two models for the prediction of students’ DWI. In light of the significance of the knowledge and awareness of Dieticians’ recommendation on DWI (as evidence in this study) and the low awareness rate existing among the students; nutrition and health promotion program on the benefits of adequate DWI by schools and health organizations is extremely important. This has the potential of improving the health of students.